diff --git a/.gitignore b/.gitignore
index e8ae399..c532c69 100644
--- a/.gitignore
+++ b/.gitignore
@@ -38,3 +38,4 @@ janus-dashboard/.vscode/
 debug_*.py
 tests/reproduction_test.rs
 tests/user_query_repro.rs
+/logs/
diff --git a/Cargo.toml b/Cargo.toml
index be221a5..dd55bf7 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -25,6 +25,9 @@ tower-http = { version = "0.5", features = ["cors", "trace"] }
 tokio-tungstenite = "0.21"
 reqwest = { version = "0.11", features = ["json"] }
 futures-util = "0.3"
+sha2 = "0.10"
+plotters = "0.3.7"
+sysinfo = "0.31.4"
 
 [lib]
 name = "janus"
diff --git a/README.md b/README.md
index 672b042..e70da15 100644
--- a/README.md
+++ b/README.md
@@ -18,6 +18,7 @@ The name comes from the Roman deity Janus, associated with transitions and with
 - Hybrid queries that mix historical and live windows
 - Extension functions for anomaly-style predicates such as thresholds, relative change, z-score, outlier checks, and trend divergence
 - Optional baseline bootstrapping for hybrid anomaly queries with `USING BASELINE <window> LAST|AGGREGATE`
+- Query-defined baselines with `DEFINE BASELINE ... ON WINDOW ... AS SELECT ...`, `USING BASELINE :name`, and `GRAPH :name { ... }` materialization templates
 - HTTP endpoints for registering, starting, stopping, listing, and deleting queries
 - WebSocket result streaming for running queries
 
@@ -28,30 +29,45 @@ Janus uses Janus-QL, a hybrid query language for querying historical and live RD
 Example:
 
 ```sparql
-PREFIX ex: <http://example.org/>
-PREFIX janus: <https://janus.rs/fn#>
-PREFIX baseline: <https://janus.rs/baseline#>
-
-REGISTER RStream ex:out AS
-SELECT ?sensor ?reading
-FROM NAMED WINDOW ex:hist ON LOG ex:store [START 1700000000000 END 1700003600000]
-FROM NAMED WINDOW ex:live ON STREAM ex:stream1 [RANGE 5000 STEP 1000]
-USING BASELINE ex:hist AGGREGATE
+PREFIX : <http://example.org/>
+
+FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60000 STEP 1000]
+FROM NAMED WINDOW :historyDay ON LOG :stream [START 0 END 86400000]
+
+DEFINE BASELINE :dayBaseline ON WINDOW :historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor :hasValue ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream :output AS
+USING BASELINE :dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
 WHERE {
-  WINDOW ex:hist {
-    ?sensor ex:mean ?mean .
-    ?sensor ex:sigma ?sigma .
+  WINDOW :liveMinute {
+    ?sensor :hasValue ?value .
   }
-  WINDOW ex:live {
-    ?sensor ex:hasReading ?reading .
+  GRAPH :dayBaseline {
+    ?sensor :dayAvgValue ?dayAvgValue .
   }
-  ?sensor baseline:mean ?mean .
-  ?sensor baseline:sigma ?sigma .
-  FILTER(janus:is_outlier(?reading, ?mean, ?sigma, 3))
 }
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
 ```
 
-`USING BASELINE` is optional. If present, Janus bootstraps baseline values from the named historical window before or during live execution:
+For query-defined baselines:
+
+- `DEFINE BASELINE` evaluates the historical baseline query before live startup over the source `LOG` window
+- `USING BASELINE :dayBaseline` tells Janus to prepare that baseline and inject the resulting quads into the live engine
+- `GRAPH :dayBaseline { ... }` is the materialization template; its concrete predicates and projected variables define the quads that are inserted
+- the live query can then use baseline variables in `SELECT`, `GROUP BY`, `HAVING`, and arithmetic expressions
+
+Legacy `USING BASELINE <window> LAST|AGGREGATE` remains available:
 
 - `LAST`: use the final historical window snapshot as baseline
 - `AGGREGATE`: merge the historical window outputs into one compact baseline
@@ -80,6 +96,7 @@ Janus uses dictionary encoding and segmented storage for high-throughput ingesti
 - Space efficiency: about 40% smaller encoded events
 
 Detailed benchmark data is in [docs/BENCHMARK_RESULTS.md](./docs/BENCHMARK_RESULTS.md).
+Current benchmark commands and scope are in [docs/BENCHMARKING.md](./docs/BENCHMARKING.md).
 
 ## Quick Start
 
diff --git a/benches/historical_fixed.rs b/benches/historical_fixed.rs
index fb03612..dda42cc 100644
--- a/benches/historical_fixed.rs
+++ b/benches/historical_fixed.rs
@@ -1,50 +1,24 @@
+mod support;
+
 use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
 use janus::{
     execution::historical_executor::HistoricalExecutor,
     parsing::janusql_parser::{SourceKind, WindowDefinition, WindowType},
     querying::oxigraph_adapter::OxigraphAdapter,
-    storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
-};
-use std::sync::{
-    atomic::{AtomicU64, Ordering},
-    Arc,
+    storage::segmented_storage::StreamingSegmentedStorage,
 };
-use std::time::{SystemTime, UNIX_EPOCH};
-
-static COUNTER: AtomicU64 = AtomicU64::new(0);
-
-fn unique_config() -> StreamingConfig {
-    let id = COUNTER.fetch_add(1, Ordering::Relaxed);
-    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_nanos();
-    StreamingConfig {
-        segment_base_path: format!("/tmp/janus_bench_fixed_{}_{}", ts, id),
-        max_batch_events: 1_000_000,
-        max_batch_age_seconds: 3600,
-        max_batch_bytes: 1_000_000_000,
-        sparse_interval: 64,
-        entries_per_index_block: 256,
-    }
-}
+use std::sync::Arc;
+use support::{populate_storage, unique_config, GRAPH_URI};
 
 /// Write N events at timestamps [1000, 1000+N) into a fresh storage.
 /// These land in the in-memory batch buffer — no flush needed before querying.
 fn setup(n: usize) -> (Arc<StreamingSegmentedStorage>, WindowDefinition) {
-    let storage = StreamingSegmentedStorage::new(unique_config()).unwrap();
-    for i in 0..n as u64 {
-        storage
-            .write_rdf(
-                1_000 + i,
-                &format!("http://example.org/sensor{}", i % 5),
-                "http://saref.etsi.org/core/hasValue",
-                &format!("{}", 20 + (i % 10)),
-                "http://example.org/graph",
-            )
-            .unwrap();
-    }
+    let storage = StreamingSegmentedStorage::new(unique_config("historical_fixed")).unwrap();
+    populate_storage(&storage, n, 1_000, 1, GRAPH_URI);
     let window = WindowDefinition {
         window_name: "w".to_string(),
         source_kind: SourceKind::Stream,
-        stream_name: "http://example.org/stream".to_string(),
+        stream_name: GRAPH_URI.to_string(),
         width: n as u64,
         slide: n as u64,
         offset: None,
@@ -55,7 +29,15 @@ fn setup(n: usize) -> (Arc<StreamingSegmentedStorage>, WindowDefinition) {
     (Arc::new(storage), window)
 }
 
-const SPARQL: &str = "SELECT ?s ?p ?o WHERE { ?s ?p ?o }";
+const SPARQL: &str = r#"
+    PREFIX ex: <http://example.org/>
+    SELECT ?sensor ?temp
+    WHERE {
+        GRAPH ex:graph1 {
+            ?sensor ex:temperature ?temp .
+        }
+    }
+"#;
 
 fn historical_fixed(c: &mut Criterion) {
     let mut group = c.benchmark_group("historical/fixed_window");
diff --git a/benches/historical_sliding.rs b/benches/historical_sliding.rs
index dc83f8a..7945fb8 100644
--- a/benches/historical_sliding.rs
+++ b/benches/historical_sliding.rs
@@ -1,30 +1,14 @@
+mod support;
+
 use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
 use janus::{
     execution::historical_executor::HistoricalExecutor,
     parsing::janusql_parser::{SourceKind, WindowDefinition, WindowType},
     querying::oxigraph_adapter::OxigraphAdapter,
-    storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
-};
-use std::sync::{
-    atomic::{AtomicU64, Ordering},
-    Arc,
+    storage::segmented_storage::StreamingSegmentedStorage,
 };
-use std::time::{SystemTime, UNIX_EPOCH};
-
-static COUNTER: AtomicU64 = AtomicU64::new(0);
-
-fn unique_config() -> StreamingConfig {
-    let id = COUNTER.fetch_add(1, Ordering::Relaxed);
-    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_nanos();
-    StreamingConfig {
-        segment_base_path: format!("/tmp/janus_bench_sliding_{}_{}", ts, id),
-        max_batch_events: 1_000_000,
-        max_batch_age_seconds: 3600,
-        max_batch_bytes: 1_000_000_000,
-        sparse_interval: 64,
-        entries_per_index_block: 256,
-    }
-}
+use std::sync::Arc;
+use support::{populate_storage, recent_base_timestamp, unique_config, GRAPH_URI};
 
 // Window config: OFFSET=10_000ms, RANGE=2_000ms, SLIDE=1_000ms
 // SlidingWindowIterator scans [now-10000, now] with 8 overlapping windows.
@@ -36,25 +20,14 @@ const DATA_START_BEFORE_NOW_MS: u64 = 8_000;
 const DATA_SPAN_MS: u64 = 6_000;
 
 fn setup(n: usize) -> (Arc<StreamingSegmentedStorage>, WindowDefinition) {
-    let now = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_millis() as u64;
-    let storage = StreamingSegmentedStorage::new(unique_config()).unwrap();
-    let n64 = n as u64;
-    for i in 0..n64 {
-        let ts = now - DATA_START_BEFORE_NOW_MS + i * DATA_SPAN_MS / n64.max(1);
-        storage
-            .write_rdf(
-                ts,
-                &format!("http://example.org/sensor{}", i % 5),
-                "http://saref.etsi.org/core/hasValue",
-                &format!("{}", 20 + (i % 10)),
-                "http://example.org/graph",
-            )
-            .unwrap();
-    }
+    let start_ts = recent_base_timestamp(DATA_START_BEFORE_NOW_MS);
+    let storage = StreamingSegmentedStorage::new(unique_config("historical_sliding")).unwrap();
+    let step_ms = (DATA_SPAN_MS / n.max(1) as u64).max(1);
+    populate_storage(&storage, n, start_ts, step_ms, GRAPH_URI);
     let window = WindowDefinition {
         window_name: "w".to_string(),
         source_kind: SourceKind::Stream,
-        stream_name: "http://example.org/stream".to_string(),
+        stream_name: GRAPH_URI.to_string(),
         width: RANGE_MS,
         slide: SLIDE_MS,
         offset: Some(OFFSET_MS),
@@ -65,7 +38,15 @@ fn setup(n: usize) -> (Arc<StreamingSegmentedStorage>, WindowDefinition) {
     (Arc::new(storage), window)
 }
 
-const SPARQL: &str = "SELECT ?s ?p ?o WHERE { ?s ?p ?o }";
+const SPARQL: &str = r#"
+    PREFIX ex: <http://example.org/>
+    SELECT ?sensor ?temp
+    WHERE {
+        GRAPH ex:graph1 {
+            ?sensor ex:temperature ?temp .
+        }
+    }
+"#;
 
 fn historical_sliding(c: &mut Criterion) {
     let mut group = c.benchmark_group("historical/sliding_window");
diff --git a/benches/hybrid_baseline.rs b/benches/hybrid_baseline.rs
new file mode 100644
index 0000000..60c6c64
--- /dev/null
+++ b/benches/hybrid_baseline.rs
@@ -0,0 +1,68 @@
+mod support;
+
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use janus::{core::RDFEvent, stream::live_stream_processing::LiveStreamProcessing};
+use std::time::Duration;
+use support::{make_sensor_event, wait_for_live_result, BASELINE_PREDICATE, STREAM_URI};
+
+const HYBRID_RSPQL: &str = r#"
+    PREFIX ex: <http://example.org/>
+    REGISTER RStream <output> AS
+    SELECT ?sensor ?liveTemp ?baselineTemp
+    FROM NAMED WINDOW ex:live ON STREAM ex:stream1 [RANGE 10000 STEP 1000]
+    WHERE {
+        WINDOW ex:live {
+            ?sensor ex:temperature ?liveTemp .
+        }
+        ?sensor ex:baselineTemperature ?baselineTemp .
+    }
+"#;
+
+fn setup_processor() -> LiveStreamProcessing {
+    let mut proc = LiveStreamProcessing::new(HYBRID_RSPQL.to_string()).unwrap();
+    proc.register_stream(STREAM_URI).unwrap();
+
+    for i in 0..5u64 {
+        proc.add_static_data(RDFEvent::new(
+            0,
+            &format!("http://example.org/sensor{i}"),
+            BASELINE_PREDICATE,
+            &format!("{}", 20 + i),
+            "",
+        ))
+        .unwrap();
+    }
+
+    proc.start_processing().unwrap();
+    proc
+}
+
+fn hybrid_baseline_join(c: &mut Criterion) {
+    let mut group = c.benchmark_group("hybrid/baseline_join");
+    group.sample_size(20);
+
+    for &n in &[1usize, 10, 100] {
+        group.bench_with_input(BenchmarkId::new("events_per_window", n), &n, |b, &n| {
+            b.iter_batched(
+                setup_processor,
+                |proc| {
+                    let n64 = n as u64;
+                    for i in 0..n64 {
+                        let ts = if n64 > 1 { i * 9_000 / (n64 - 1) } else { 0 };
+                        proc.add_event(STREAM_URI, make_sensor_event(ts, i, "")).unwrap();
+                    }
+
+                    proc.close_stream(STREAM_URI, 20_000).unwrap();
+                    let result = wait_for_live_result(&proc, Duration::from_secs(10));
+                    black_box(result)
+                },
+                criterion::BatchSize::SmallInput,
+            );
+        });
+    }
+
+    group.finish();
+}
+
+criterion_group!(benches, hybrid_baseline_join);
+criterion_main!(benches);
diff --git a/benches/janusql_e2e.rs b/benches/janusql_e2e.rs
new file mode 100644
index 0000000..b892d81
--- /dev/null
+++ b/benches/janusql_e2e.rs
@@ -0,0 +1,339 @@
+mod support;
+
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use futures_util::StreamExt;
+use janus::{
+    api::janus_api::JanusApi,
+    http::server::{create_server_with_state, AppState},
+    parsing::janusql_parser::JanusQLParser,
+    registry::query_registry::QueryRegistry,
+    storage::segmented_storage::StreamingSegmentedStorage,
+};
+use reqwest::Client;
+use serde_json::{json, Value};
+use std::{fs, path::PathBuf, sync::Arc, time::Duration as StdDuration};
+use tempfile::TempDir;
+use tokio::{net::TcpListener, runtime::Runtime, task::JoinHandle, time::Duration};
+use tokio_tungstenite::connect_async;
+
+use support::{
+    populate_storage, recent_base_timestamp, unique_config, GRAPH_URI, TEMPERATURE_PREDICATE,
+};
+
+struct BenchServer {
+    base_url: String,
+    ws_base_url: String,
+    client: Client,
+    storage_dir: PathBuf,
+    _temp_dir: TempDir,
+    server_task: JoinHandle<()>,
+}
+
+impl Drop for BenchServer {
+    fn drop(&mut self) {
+        self.server_task.abort();
+    }
+}
+
+async fn spawn_server(
+    preload_events: usize,
+    preload_start_timestamp: u64,
+    preload_step_ms: u64,
+) -> BenchServer {
+    let temp_dir = TempDir::new().expect("failed to create benchmark temp dir");
+    let storage_dir = temp_dir.path().to_path_buf();
+    let storage = StreamingSegmentedStorage::new(unique_config("janusql_e2e"))
+        .expect("failed to create benchmark storage");
+
+    if preload_events > 0 {
+        populate_storage(
+            &storage,
+            preload_events,
+            preload_start_timestamp,
+            preload_step_ms,
+            GRAPH_URI,
+        );
+        storage.flush().expect("failed to flush benchmark storage");
+    }
+
+    let storage = Arc::new(storage);
+    let registry = Arc::new(QueryRegistry::new());
+    let janus_api = Arc::new(
+        JanusApi::new(
+            JanusQLParser::new().expect("failed to create parser"),
+            Arc::clone(&registry),
+            Arc::clone(&storage),
+        )
+        .expect("failed to create api"),
+    );
+
+    let (app, _state): (_, Arc<AppState>) = create_server_with_state(janus_api, registry, storage);
+    let listener = TcpListener::bind("127.0.0.1:0")
+        .await
+        .expect("failed to bind benchmark listener");
+    let addr = listener.local_addr().expect("failed to read benchmark listener addr");
+    let server_task = tokio::spawn(async move {
+        axum::serve(listener, app).await.expect("benchmark server crashed");
+    });
+
+    tokio::time::sleep(Duration::from_millis(25)).await;
+
+    BenchServer {
+        base_url: format!("http://{}", addr),
+        ws_base_url: format!("ws://{}", addr),
+        client: Client::new(),
+        storage_dir,
+        _temp_dir: temp_dir,
+        server_task,
+    }
+}
+
+fn historical_sliding_query(query_id: &str, graph_uri: &str) -> Value {
+    json!({
+        "query_id": query_id,
+        "janusql": format!(
+            r#"
+            PREFIX ex: <http://example.org/>
+
+            SELECT ?sensor ?temp
+
+            FROM NAMED WINDOW ex:hist ON STREAM <{graph_uri}> [OFFSET 12000 RANGE 2000 STEP 250]
+
+            WHERE {{
+                WINDOW ex:hist {{
+                    ?sensor ex:temperature ?temp .
+                }}
+            }}
+            "#
+        )
+    })
+}
+
+fn historical_fixed_query(query_id: &str, graph_uri: &str, start: u64, end: u64) -> Value {
+    json!({
+        "query_id": query_id,
+        "janusql": format!(
+            r#"
+            PREFIX ex: <http://example.org/>
+
+            SELECT ?sensor ?temp
+
+            FROM NAMED WINDOW ex:hist ON STREAM <{graph_uri}> [START {start} END {end}]
+
+            WHERE {{
+                WINDOW ex:hist {{
+                    ?sensor ex:temperature ?temp .
+                }}
+            }}
+            "#
+        )
+    })
+}
+
+async fn wait_for_ws_result(ws_base_url: &str, query_id: &str) {
+    let (mut socket, _) = connect_async(format!("{ws_base_url}/api/queries/{query_id}/results"))
+        .await
+        .expect("websocket should connect");
+
+    let message = tokio::time::timeout(Duration::from_secs(2), socket.next())
+        .await
+        .expect("timed out waiting for websocket result")
+        .expect("websocket closed unexpectedly")
+        .expect("websocket message failed");
+
+    let text = message.into_text().expect("websocket payload should be text");
+    let body: Value = serde_json::from_str(&text).expect("websocket payload should be valid json");
+    assert_eq!(body["type"], "result");
+    assert!(
+        body["bindings"].as_array().is_some_and(|bindings| !bindings.is_empty()),
+        "expected at least one binding in websocket result"
+    );
+}
+
+async fn cleanup_query(server: &BenchServer, query_id: &str) {
+    let stop_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/stop", server.base_url))
+        .send()
+        .await
+        .expect("stop request failed");
+    assert!(stop_response.status().is_success(), "stop response should succeed");
+
+    let delete_response = server
+        .client
+        .delete(format!("{}/api/queries/{query_id}", server.base_url))
+        .send()
+        .await
+        .expect("delete request failed");
+    assert!(delete_response.status().is_success(), "delete response should succeed");
+}
+
+async fn bench_preloaded_historical(server: &BenchServer, query_id: &str) -> StdDuration {
+    let register_response = server
+        .client
+        .post(format!("{}/api/queries", server.base_url))
+        .json(&historical_sliding_query(query_id, GRAPH_URI))
+        .send()
+        .await
+        .expect("register request failed");
+    assert!(register_response.status().is_success());
+
+    let started_at = std::time::Instant::now();
+    let start_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/start", server.base_url))
+        .send()
+        .await
+        .expect("start request failed");
+    assert!(start_response.status().is_success());
+
+    wait_for_ws_result(&server.ws_base_url, query_id).await;
+    let elapsed = started_at.elapsed();
+
+    cleanup_query(server, query_id).await;
+    elapsed
+}
+
+fn replay_input_contents(graph_uri: &str, start_timestamp: u64, event_count: usize) -> String {
+    let mut contents = String::new();
+    for i in 0..event_count as u64 {
+        contents.push_str(&format!(
+            "{} <http://example.org/sensor{}> <{}> \"{}\" <{}> .\n",
+            start_timestamp + i,
+            i % 5,
+            TEMPERATURE_PREDICATE,
+            20 + (i % 10),
+            graph_uri
+        ));
+    }
+    contents
+}
+
+async fn wait_for_replay_completion(server: &BenchServer) {
+    for _ in 0..100 {
+        let response = server
+            .client
+            .get(format!("{}/api/replay/status", server.base_url))
+            .send()
+            .await
+            .expect("replay status request failed");
+        assert!(response.status().is_success());
+        let body: Value = response.json().await.expect("invalid replay status response");
+        if body["is_running"] == Value::Bool(false) {
+            return;
+        }
+        tokio::time::sleep(Duration::from_millis(20)).await;
+    }
+
+    panic!("replay did not complete within timeout");
+}
+
+async fn bench_replay_historical(
+    server: &BenchServer,
+    query_id: &str,
+    graph_uri: &str,
+    start_timestamp: u64,
+    event_count: usize,
+) -> StdDuration {
+    let replay_file = server.storage_dir.join(format!("{query_id}_replay.nq"));
+    fs::write(&replay_file, replay_input_contents(graph_uri, start_timestamp, event_count))
+        .expect("failed to write replay input file");
+
+    let started_at = std::time::Instant::now();
+    let replay_response = server
+        .client
+        .post(format!("{}/api/replay/start", server.base_url))
+        .json(&json!({
+            "input_file": replay_file.to_string_lossy().to_string(),
+            "broker_type": "none",
+            "topics": ["sensors"],
+            "rate_of_publishing": 0,
+            "loop_file": false,
+            "add_timestamps": false
+        }))
+        .send()
+        .await
+        .expect("replay start request failed");
+    assert!(replay_response.status().is_success());
+
+    wait_for_replay_completion(server).await;
+
+    let register_response = server
+        .client
+        .post(format!("{}/api/queries", server.base_url))
+        .json(&historical_fixed_query(
+            query_id,
+            graph_uri,
+            start_timestamp,
+            start_timestamp + event_count as u64,
+        ))
+        .send()
+        .await
+        .expect("register request failed");
+    assert!(register_response.status().is_success());
+
+    let start_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/start", server.base_url))
+        .send()
+        .await
+        .expect("start request failed");
+    assert!(start_response.status().is_success());
+
+    wait_for_ws_result(&server.ws_base_url, query_id).await;
+    let elapsed = started_at.elapsed();
+
+    cleanup_query(server, query_id).await;
+    elapsed
+}
+
+fn janusql_e2e(c: &mut Criterion) {
+    let runtime = Runtime::new().expect("failed to create benchmark runtime");
+    let mut group = c.benchmark_group("janusql_e2e/http_first_result");
+    group.sample_size(20);
+
+    for &events in &[1_000usize, 10_000] {
+        group.bench_with_input(
+            BenchmarkId::new("historical_preloaded", events),
+            &events,
+            |b, &events| {
+                b.iter_batched(
+                    || {
+                        let start_ts = recent_base_timestamp(9_000);
+                        runtime.block_on(spawn_server(events, start_ts, 1))
+                    },
+                    |server| {
+                        let query_id = format!("e2e_hist_preloaded_{events}");
+                        black_box(runtime.block_on(bench_preloaded_historical(&server, &query_id)))
+                    },
+                    criterion::BatchSize::SmallInput,
+                );
+            },
+        );
+    }
+
+    for &events in &[100usize, 1_000] {
+        group.bench_with_input(
+            BenchmarkId::new("historical_via_replay", events),
+            &events,
+            |b, &events| {
+                b.iter_batched(
+                    || runtime.block_on(spawn_server(0, 0, 1)),
+                    |server| {
+                        let start_ts = 1_000_000 + (events as u64 * 10);
+                        let query_id = format!("e2e_hist_replay_{events}");
+                        black_box(runtime.block_on(bench_replay_historical(
+                            &server, &query_id, GRAPH_URI, start_ts, events,
+                        )))
+                    },
+                    criterion::BatchSize::SmallInput,
+                );
+            },
+        );
+    }
+
+    group.finish();
+}
+
+criterion_group!(benches, janusql_e2e);
+criterion_main!(benches);
diff --git a/benches/janusql_live_mqtt_e2e.rs b/benches/janusql_live_mqtt_e2e.rs
new file mode 100644
index 0000000..4b4f858
--- /dev/null
+++ b/benches/janusql_live_mqtt_e2e.rs
@@ -0,0 +1,408 @@
+mod support;
+
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use futures_util::StreamExt;
+use janus::{
+    api::janus_api::JanusApi,
+    http::server::{create_server_with_state, AppState},
+    parsing::janusql_parser::JanusQLParser,
+    registry::query_registry::QueryRegistry,
+    storage::segmented_storage::StreamingSegmentedStorage,
+};
+use reqwest::Client;
+use rumqttc::{AsyncClient, MqttOptions, QoS};
+use serde_json::{json, Value};
+use std::{sync::Arc, time::Duration as StdDuration};
+use tokio::{net::TcpListener, runtime::Runtime, task::JoinHandle, time::Duration};
+use tokio_tungstenite::{connect_async, MaybeTlsStream, WebSocketStream};
+
+use support::{recent_base_timestamp, unique_config, BASELINE_PREDICATE, GRAPH_URI};
+
+const DEFAULT_MQTT_HOST: &str = "127.0.0.1";
+const DEFAULT_MQTT_PORT: u16 = 1883;
+const DEFAULT_MQTT_TOPIC: &str = "sensors";
+const BASELINE_NS: &str = "https://janus.rs/baseline#";
+const HYBRID_BASELINE_START: u64 = 1_700_000_000_000;
+const HYBRID_BASELINE_END: u64 = HYBRID_BASELINE_START + 5_000;
+const LIVE_WINDOW_RANGE_MS: u64 = 50;
+const LIVE_WINDOW_STEP_MS: u64 = 10;
+const MQTT_EVENT_SPACING_MS: u64 = 15;
+const MQTT_SENTINEL_ADVANCE_MS: u64 = 75;
+
+struct BenchServer {
+    base_url: String,
+    ws_base_url: String,
+    client: Client,
+    server_task: JoinHandle<()>,
+}
+
+impl Drop for BenchServer {
+    fn drop(&mut self) {
+        self.server_task.abort();
+    }
+}
+
+#[derive(Clone)]
+struct MqttConfig {
+    host: String,
+    port: u16,
+    topic: String,
+    stream_uri: String,
+}
+
+impl MqttConfig {
+    fn from_env() -> Self {
+        let host = std::env::var("JANUS_BENCH_MQTT_HOST")
+            .unwrap_or_else(|_| DEFAULT_MQTT_HOST.to_string());
+
+        let port = std::env::var("JANUS_BENCH_MQTT_PORT")
+            .ok()
+            .and_then(|v| v.parse::<u16>().ok())
+            .unwrap_or(DEFAULT_MQTT_PORT);
+
+        let topic = std::env::var("JANUS_BENCH_MQTT_TOPIC")
+            .unwrap_or_else(|_| DEFAULT_MQTT_TOPIC.to_string());
+
+        let stream_uri = std::env::var("JANUS_BENCH_MQTT_STREAM_URI")
+            .unwrap_or_else(|_| format!("mqtt://{}:{}/{}", host, port, topic));
+
+        Self { host, port, topic, stream_uri }
+    }
+}
+
+async fn spawn_server() -> BenchServer {
+    let storage = StreamingSegmentedStorage::new(unique_config("janusql_live_mqtt_e2e"))
+        .expect("failed to create benchmark storage");
+    populate_hybrid_baseline_storage(&storage);
+    storage.flush().expect("failed to flush benchmark storage");
+    let storage = Arc::new(storage);
+    let registry = Arc::new(QueryRegistry::new());
+    let janus_api = Arc::new(
+        JanusApi::new(
+            JanusQLParser::new().expect("failed to create parser"),
+            Arc::clone(&registry),
+            Arc::clone(&storage),
+        )
+        .expect("failed to create api"),
+    );
+
+    let (app, _state): (_, Arc<AppState>) = create_server_with_state(janus_api, registry, storage);
+    let listener = TcpListener::bind("127.0.0.1:0")
+        .await
+        .expect("failed to bind benchmark listener");
+    let addr = listener.local_addr().expect("failed to read benchmark listener addr");
+
+    let server_task = tokio::spawn(async move {
+        axum::serve(listener, app).await.expect("benchmark server crashed");
+    });
+
+    tokio::time::sleep(Duration::from_millis(50)).await;
+
+    BenchServer {
+        base_url: format!("http://{}", addr),
+        ws_base_url: format!("ws://{}", addr),
+        client: Client::new(),
+        server_task,
+    }
+}
+
+fn live_query(query_id: &str, stream_uri: &str) -> Value {
+    json!({
+        "query_id": query_id,
+        "janusql": format!(
+            r#"
+            PREFIX ex: <http://example.org/>
+
+            SELECT ?sensor ?temp
+            FROM NAMED WINDOW ex:live ON STREAM <{stream_uri}> [RANGE {LIVE_WINDOW_RANGE_MS} STEP {LIVE_WINDOW_STEP_MS}]
+            WHERE {{
+                WINDOW ex:live {{
+                    ?sensor ex:temperature ?temp .
+                }}
+            }}
+            "#
+        )
+    })
+}
+
+fn hybrid_query(query_id: &str, stream_uri: &str) -> Value {
+    json!({
+        "query_id": query_id,
+        "janusql": format!(
+            r#"
+            PREFIX ex: <http://example.org/>
+            PREFIX baseline: <{BASELINE_NS}>
+
+            SELECT ?sensor ?liveTemp ?baselineTemp
+            FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START {HYBRID_BASELINE_START} END {HYBRID_BASELINE_END}]
+            FROM NAMED WINDOW ex:live ON STREAM <{stream_uri}> [RANGE {LIVE_WINDOW_RANGE_MS} STEP {LIVE_WINDOW_STEP_MS}]
+            USING BASELINE ex:hist AGGREGATE
+            WHERE {{
+                WINDOW ex:hist {{
+                    ?sensor ex:baselineTemperature ?baselineTemp .
+                }}
+                WINDOW ex:live {{
+                    ?sensor ex:temperature ?liveTemp .
+                }}
+                ?sensor baseline:baselineTemp ?baselineTemp .
+            }}
+            "#
+        )
+    })
+}
+
+fn populate_hybrid_baseline_storage(storage: &StreamingSegmentedStorage) {
+    for i in 0..5u64 {
+        storage
+            .write_rdf(
+                HYBRID_BASELINE_START + i,
+                &format!("http://example.org/sensor{i}"),
+                BASELINE_PREDICATE,
+                &format!("{}", 20 + i),
+                GRAPH_URI,
+            )
+            .expect("failed to write baseline benchmark data");
+    }
+}
+
+async fn open_result_socket(
+    ws_base_url: &str,
+    query_id: &str,
+) -> WebSocketStream<MaybeTlsStream<tokio::net::TcpStream>> {
+    let (socket, _) = connect_async(format!("{ws_base_url}/api/queries/{query_id}/results"))
+        .await
+        .expect("websocket should connect");
+    socket
+}
+
+async fn wait_for_ws_result(socket: &mut WebSocketStream<MaybeTlsStream<tokio::net::TcpStream>>) {
+    let message = tokio::time::timeout(Duration::from_secs(10), socket.next())
+        .await
+        .expect("timed out waiting for websocket result")
+        .expect("websocket closed unexpectedly")
+        .expect("websocket message failed");
+
+    let text = message.into_text().expect("websocket payload should be text");
+    let body: Value = serde_json::from_str(&text).expect("websocket payload should be valid json");
+    assert_eq!(body["type"], "result");
+    assert!(
+        body["bindings"].as_array().is_some_and(|bindings| !bindings.is_empty()),
+        "expected at least one binding in websocket result"
+    );
+}
+
+async fn wait_for_query_status(server: &BenchServer, query_id: &str, expected_status: &str) {
+    for _ in 0..100 {
+        let response = server
+            .client
+            .get(format!("{}/api/queries/{query_id}", server.base_url))
+            .send()
+            .await
+            .expect("query status request failed");
+        assert!(response.status().is_success(), "query details response should succeed");
+        let body: Value = response.json().await.expect("invalid query details response");
+        if body["status"] == Value::String(expected_status.to_string()) {
+            return;
+        }
+        tokio::time::sleep(Duration::from_millis(20)).await;
+    }
+
+    panic!("query did not reach status '{expected_status}' within timeout");
+}
+
+async fn cleanup_query(server: &BenchServer, query_id: &str) {
+    let stop_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/stop", server.base_url))
+        .send()
+        .await
+        .expect("stop request failed");
+    assert!(stop_response.status().is_success(), "stop response should succeed");
+
+    let delete_response = server
+        .client
+        .delete(format!("{}/api/queries/{query_id}", server.base_url))
+        .send()
+        .await
+        .expect("delete request failed");
+    assert!(delete_response.status().is_success(), "delete response should succeed");
+}
+
+fn build_mqtt_payload(ts: u64, sensor_idx: usize, temp: i64) -> String {
+    format!(
+        "{} <http://example.org/sensor{}> <http://example.org/temperature> \"{}\" <http://example.org/graph1> .",
+        ts, sensor_idx, temp
+    )
+}
+
+fn build_mqtt_sentinel_payload(ts: u64) -> String {
+    format!(
+        "{ts} <urn:rsp:sentinel:subject> <urn:rsp:sentinel:predicate> <urn:rsp:sentinel:object> <http://example.org/graph1> ."
+    )
+}
+
+async fn publish_events(cfg: &MqttConfig, events: usize, base_ts: u64) {
+    let client_id = format!("janus_bench_pub_{}_{}", std::process::id(), base_ts);
+    let mut options = MqttOptions::new(client_id, cfg.host.clone(), cfg.port);
+    options.set_keep_alive(Duration::from_secs(5));
+
+    let (client, mut eventloop) = AsyncClient::new(options, 32);
+
+    // Prime connection/sub-acks processing path.
+    tokio::spawn(async move {
+        // Keep polling briefly; benchmark will be short-lived.
+        for _ in 0..200usize {
+            let _ = tokio::time::timeout(Duration::from_millis(50), eventloop.poll()).await;
+        }
+    });
+
+    // Give server subscriber a moment to subscribe before publish burst.
+    tokio::time::sleep(Duration::from_millis(80)).await;
+
+    for i in 0..events {
+        let payload = build_mqtt_payload(base_ts + i as u64, i % 5, 20 + (i % 10) as i64);
+        client
+            .publish(cfg.topic.clone(), QoS::AtLeastOnce, false, payload)
+            .await
+            .expect("failed to publish mqtt event");
+        tokio::time::sleep(Duration::from_millis(MQTT_EVENT_SPACING_MS)).await;
+    }
+
+    tokio::time::sleep(Duration::from_millis(MQTT_SENTINEL_ADVANCE_MS)).await;
+    client
+        .publish(
+            cfg.topic.clone(),
+            QoS::AtLeastOnce,
+            false,
+            build_mqtt_sentinel_payload(base_ts + events as u64 + 1),
+        )
+        .await
+        .expect("failed to publish mqtt sentinel event");
+    tokio::time::sleep(Duration::from_millis(30)).await;
+}
+
+async fn bench_live_mqtt_first_result(
+    server: &BenchServer,
+    mqtt_cfg: &MqttConfig,
+    query_id: &str,
+    publish_events_count: usize,
+) -> StdDuration {
+    let register_response = server
+        .client
+        .post(format!("{}/api/queries", server.base_url))
+        .json(&live_query(query_id, &mqtt_cfg.stream_uri))
+        .send()
+        .await
+        .expect("register request failed");
+    assert!(register_response.status().is_success());
+
+    let start_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/start", server.base_url))
+        .send()
+        .await
+        .expect("start request failed");
+    assert!(start_response.status().is_success());
+
+    let started_at = std::time::Instant::now();
+    let mut socket = open_result_socket(&server.ws_base_url, query_id).await;
+    let publish_ts = recent_base_timestamp(0);
+    publish_events(mqtt_cfg, publish_events_count, publish_ts).await;
+    wait_for_ws_result(&mut socket).await;
+    let elapsed = started_at.elapsed();
+
+    cleanup_query(server, query_id).await;
+    elapsed
+}
+
+async fn bench_hybrid_mqtt_first_result(
+    server: &BenchServer,
+    mqtt_cfg: &MqttConfig,
+    query_id: &str,
+    publish_events_count: usize,
+) -> StdDuration {
+    let register_response = server
+        .client
+        .post(format!("{}/api/queries", server.base_url))
+        .json(&hybrid_query(query_id, &mqtt_cfg.stream_uri))
+        .send()
+        .await
+        .expect("register request failed");
+    assert!(register_response.status().is_success());
+
+    let start_response = server
+        .client
+        .post(format!("{}/api/queries/{query_id}/start", server.base_url))
+        .send()
+        .await
+        .expect("start request failed");
+    assert!(start_response.status().is_success());
+
+    let started_at = std::time::Instant::now();
+    wait_for_query_status(server, query_id, "Running").await;
+    let mut socket = open_result_socket(&server.ws_base_url, query_id).await;
+    let publish_ts = recent_base_timestamp(0);
+    publish_events(mqtt_cfg, publish_events_count, publish_ts).await;
+    wait_for_ws_result(&mut socket).await;
+    let elapsed = started_at.elapsed();
+
+    cleanup_query(server, query_id).await;
+    elapsed
+}
+
+fn janusql_live_mqtt_e2e(c: &mut Criterion) {
+    let runtime = Runtime::new().expect("failed to create benchmark runtime");
+    let mqtt_cfg = MqttConfig::from_env();
+
+    let mut group = c.benchmark_group("janusql_e2e/live_mqtt_http_first_result");
+    group.sample_size(10);
+
+    for &events in &[1usize, 10, 50] {
+        group.bench_with_input(
+            BenchmarkId::new("mqtt_live_first_result", events),
+            &events,
+            |b, &events| {
+                b.iter_batched(
+                    || runtime.block_on(spawn_server()),
+                    |server| {
+                        let query_id =
+                            format!("e2e_live_mqtt_{}_{}", events, recent_base_timestamp(0));
+                        black_box(runtime.block_on(bench_live_mqtt_first_result(
+                            &server, &mqtt_cfg, &query_id, events,
+                        )))
+                    },
+                    criterion::BatchSize::SmallInput,
+                );
+            },
+        );
+    }
+    group.finish();
+
+    let mut hybrid_group = c.benchmark_group("janusql_e2e/hybrid_mqtt_http_first_result");
+    hybrid_group.sample_size(10);
+
+    for &events in &[1usize, 10, 50] {
+        hybrid_group.bench_with_input(
+            BenchmarkId::new("mqtt_hybrid_first_result", events),
+            &events,
+            |b, &events| {
+                b.iter_batched(
+                    || runtime.block_on(spawn_server()),
+                    |server| {
+                        let query_id =
+                            format!("e2e_hybrid_mqtt_{}_{}", events, recent_base_timestamp(0));
+                        black_box(runtime.block_on(bench_hybrid_mqtt_first_result(
+                            &server, &mqtt_cfg, &query_id, events,
+                        )))
+                    },
+                    criterion::BatchSize::SmallInput,
+                );
+            },
+        );
+    }
+
+    hybrid_group.finish();
+}
+
+criterion_group!(benches, janusql_live_mqtt_e2e);
+criterion_main!(benches);
diff --git a/benches/live_injection.rs b/benches/live_injection.rs
index 32714cc..09c1c03 100644
--- a/benches/live_injection.rs
+++ b/benches/live_injection.rs
@@ -1,8 +1,9 @@
-use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
-use janus::{core::RDFEvent, stream::live_stream_processing::LiveStreamProcessing};
-use std::time::Instant;
+mod support;
 
-const STREAM_URI: &str = "http://example.org/stream1";
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use janus::stream::live_stream_processing::LiveStreamProcessing;
+use std::time::Duration;
+use support::{make_sensor_event, wait_for_live_result, STREAM_URI};
 
 // RSP-QL query: 10s range, 1s step window over stream1
 const RSPQL: &str = r#"
@@ -15,33 +16,6 @@ const RSPQL: &str = r#"
     }
 "#;
 
-fn make_event(timestamp_ms: u64, i: u64) -> RDFEvent {
-    RDFEvent::new(
-        timestamp_ms,
-        &format!("http://example.org/sensor{}", i % 5),
-        "http://saref.etsi.org/core/hasValue",
-        &format!("{}", 20 + (i % 10)),
-        "",
-    )
-}
-
-/// Wait for the first live result with a 10-second hard deadline.
-/// Panics with a clear message if nothing arrives — indicates the RSP engine
-/// is not emitting results for the injected events.
-fn wait_for_result(proc: &LiveStreamProcessing) -> rsp_rs::BindingWithTimestamp {
-    let deadline = Instant::now() + std::time::Duration::from_secs(10);
-    loop {
-        if let Some(result) = proc.try_receive_result().unwrap() {
-            return result;
-        }
-        assert!(
-            Instant::now() < deadline,
-            "live_injection: no result within 10s — RSP engine did not emit for injected events"
-        );
-        std::thread::yield_now();
-    }
-}
-
 fn live_injection(c: &mut Criterion) {
     let mut group = c.benchmark_group("live/event_injection");
     // Lower sample size: each iteration spawns an RSP engine thread
@@ -61,12 +35,12 @@ fn live_injection(c: &mut Criterion) {
                     let n64 = n as u64;
                     for i in 0..n64 {
                         let ts = if n64 > 1 { i * 9_000 / (n64 - 1) } else { 0 };
-                        proc.add_event(STREAM_URI, make_event(ts, i)).unwrap();
+                        proc.add_event(STREAM_URI, make_sensor_event(ts, i, "")).unwrap();
                     }
                     // Sentinel at 20_000 ms closes all open windows
-                    proc.add_event(STREAM_URI, make_event(20_000, 999)).unwrap();
+                    proc.add_event(STREAM_URI, make_sensor_event(20_000, 999, "")).unwrap();
                     // Block until first result arrives
-                    black_box(wait_for_result(&proc))
+                    black_box(wait_for_live_result(&proc, Duration::from_secs(10)))
                 },
                 criterion::BatchSize::SmallInput,
             );
diff --git a/benches/storage_write.rs b/benches/storage_write.rs
index d990756..bebf124 100644
--- a/benches/storage_write.rs
+++ b/benches/storage_write.rs
@@ -1,23 +1,8 @@
-use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
-use janus::storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig};
-use std::sync::atomic::{AtomicU64, Ordering};
-use std::time::{SystemTime, UNIX_EPOCH};
-
-static COUNTER: AtomicU64 = AtomicU64::new(0);
+mod support;
 
-fn unique_config() -> StreamingConfig {
-    let id = COUNTER.fetch_add(1, Ordering::Relaxed);
-    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_nanos();
-    StreamingConfig {
-        segment_base_path: format!("/tmp/janus_bench_write_{}_{}", ts, id),
-        // Large thresholds so no flush happens during measurement
-        max_batch_events: 1_000_000,
-        max_batch_age_seconds: 3600,
-        max_batch_bytes: 1_000_000_000,
-        sparse_interval: 64,
-        entries_per_index_block: 256,
-    }
-}
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+use janus::storage::segmented_storage::StreamingSegmentedStorage;
+use support::{make_sensor_event, unique_config, GRAPH_URI};
 
 fn storage_write(c: &mut Criterion) {
     let mut group = c.benchmark_group("storage/write_throughput");
@@ -26,18 +11,11 @@ fn storage_write(c: &mut Criterion) {
         group.throughput(Throughput::Elements(n as u64));
         group.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &n| {
             b.iter_batched(
-                || StreamingSegmentedStorage::new(unique_config()).unwrap(),
+                || StreamingSegmentedStorage::new(unique_config("write")).unwrap(),
                 |storage| {
                     for i in 0..n as u64 {
-                        storage
-                            .write_rdf(
-                                black_box(1_000 + i),
-                                &format!("http://example.org/sensor{}", i % 5),
-                                "http://saref.etsi.org/core/hasValue",
-                                &format!("{}", 20 + (i % 10)),
-                                "http://example.org/graph",
-                            )
-                            .unwrap();
+                        let event = make_sensor_event(1_000 + i, i, GRAPH_URI);
+                        storage.write_rdf_event(black_box(event)).unwrap();
                     }
                 },
                 criterion::BatchSize::SmallInput,
diff --git a/benches/support/mod.rs b/benches/support/mod.rs
new file mode 100644
index 0000000..463f9e4
--- /dev/null
+++ b/benches/support/mod.rs
@@ -0,0 +1,77 @@
+#![allow(dead_code)]
+
+use janus::{
+    core::RDFEvent,
+    storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
+    stream::live_stream_processing::LiveStreamProcessing,
+};
+use rsp_rs::BindingWithTimestamp;
+use std::sync::atomic::{AtomicU64, Ordering};
+use std::time::{Duration, Instant, SystemTime, UNIX_EPOCH};
+
+pub const GRAPH_URI: &str = "http://example.org/graph1";
+pub const STREAM_URI: &str = "http://example.org/stream1";
+pub const TEMPERATURE_PREDICATE: &str = "http://example.org/temperature";
+pub const BASELINE_PREDICATE: &str = "http://example.org/baselineTemperature";
+
+static COUNTER: AtomicU64 = AtomicU64::new(0);
+
+pub fn unique_config(prefix: &str) -> StreamingConfig {
+    let id = COUNTER.fetch_add(1, Ordering::Relaxed);
+    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_nanos();
+    StreamingConfig {
+        segment_base_path: format!("/tmp/janus_bench_{prefix}_{ts}_{id}"),
+        max_batch_events: 1_000_000,
+        max_batch_age_seconds: 3600,
+        max_batch_bytes: 1_000_000_000,
+        sparse_interval: 64,
+        entries_per_index_block: 256,
+    }
+}
+
+pub fn make_sensor_event(timestamp_ms: u64, index: u64, graph: &str) -> RDFEvent {
+    RDFEvent::new(
+        timestamp_ms,
+        &format!("http://example.org/sensor{}", index % 5),
+        TEMPERATURE_PREDICATE,
+        &format!("{}", 20 + (index % 10)),
+        graph,
+    )
+}
+
+pub fn populate_storage(
+    storage: &StreamingSegmentedStorage,
+    event_count: usize,
+    start_timestamp_ms: u64,
+    step_ms: u64,
+    graph: &str,
+) {
+    for i in 0..event_count as u64 {
+        let event = make_sensor_event(start_timestamp_ms + i * step_ms, i, graph);
+        storage.write_rdf_event(event).unwrap();
+    }
+}
+
+pub fn recent_base_timestamp(offset_ms: u64) -> u64 {
+    let now = SystemTime::now().duration_since(UNIX_EPOCH).unwrap().as_millis() as u64;
+    now.saturating_sub(offset_ms)
+}
+
+pub fn wait_for_live_result(
+    processor: &LiveStreamProcessing,
+    timeout: Duration,
+) -> BindingWithTimestamp {
+    let deadline = Instant::now() + timeout;
+    loop {
+        if let Some(result) = processor.try_receive_result().unwrap() {
+            return result;
+        }
+
+        assert!(
+            Instant::now() < deadline,
+            "benchmark timed out waiting for a live result after {:?}",
+            timeout
+        );
+        std::thread::yield_now();
+    }
+}
diff --git a/docs/BASELINES.md b/docs/BASELINES.md
index 4e0f7c5..eb30418 100644
--- a/docs/BASELINES.md
+++ b/docs/BASELINES.md
@@ -4,13 +4,18 @@ Baseline support in Janus is meant for hybrid anomaly-style queries where histor
 
 It is not a full hybrid-state engine.
 
+Janus currently supports two baseline paths:
+
+- legacy `USING BASELINE <historical-window> LAST|AGGREGATE`
+- query-defined `DEFINE BASELINE :name ON WINDOW :history AS SELECT ...` together with `USING BASELINE :name`
+
 ## What Baseline Bootstrap Does
 
 When a query has:
 
 - at least one historical window
 - at least one live window
-- a baseline-aware query shape, typically with `baseline:*` joins
+- a baseline-aware query shape
 
 Janus can evaluate the historical side, collapse the result into compact baseline statements, and insert those statements into the live processor as static data.
 
@@ -37,6 +42,73 @@ If the clause is missing, registration can still provide:
 
 The query-level clause takes precedence when present.
 
+For query-defined baselines, `USING BASELINE :name` means:
+
+1. evaluate the generated historical baseline query over its source `LOG` window
+2. materialize the resulting bindings through the matching `GRAPH :name { ... }` template
+3. insert the resulting RDF quads into the live RSP engine static store before live startup
+4. allow the live query to bind those values during live execution
+
+## Canonical Query-Defined Example
+
+```sparql
+PREFIX : <http://example.org/>
+
+FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60000 STEP 1000]
+FROM NAMED WINDOW :historyDay ON LOG :stream [START 0 END 86400000]
+
+DEFINE BASELINE :dayBaseline ON WINDOW :historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor :hasValue ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream :output AS
+USING BASELINE :dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {
+  WINDOW :liveMinute {
+    ?sensor :hasValue ?value .
+  }
+  GRAPH :dayBaseline {
+    ?sensor :dayAvgValue ?dayAvgValue .
+  }
+}
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
+```
+
+This compares the 1-minute live average against the 1-day historical average for each sensor. The historical `AVG` result is turned into static RDF before the live query starts, so `?dayAvgValue` is an ordinary live-side binding once the query runs.
+
+## Query-Defined Materialization Rule
+
+Current rule in v0.1:
+
+- the `GRAPH :baselineName { ... }` block defines the RDF shape that is inserted
+- the baseline query must project every variable used by that template
+- template predicates must be concrete IRIs
+- template subjects must resolve to an IRI or blank node
+
+Example:
+
+- `?sensor = :s1`
+- `?dayAvgValue = 42.0`
+
+becomes:
+
+```trig
+GRAPH :dayBaseline {
+  :s1 :dayAvgValue 42.0 .
+}
+```
+
+This is why Janus uses the `GRAPH` template rather than trying to infer quads from `SELECT` projection aliases: the template states the exact RDF layout that should be injected, while `SELECT` only describes the available bindings.
+
 ## LAST vs AGGREGATE
 
 ### LAST
@@ -73,11 +145,11 @@ In practice:
 - fixed historical baseline is usually the simplest and clearest baseline path
 - historical sliding baseline is more advanced and can cost more at startup
 
-## Async Warm-Up
+## Startup Behavior
 
-Janus now warms baseline state asynchronously.
+Legacy window baselines warm asynchronously.
 
-Behavior:
+Behavior for `USING BASELINE <window> LAST|AGGREGATE`:
 
 1. live execution starts immediately
 2. query status becomes `WarmingBaseline`
@@ -90,6 +162,13 @@ Effect on query results:
 - a live query that depends on baseline joins typically produces no matches until the baseline is ready
 - once baseline static data exists, future live evaluations can match those joins
 
+Behavior for query-defined baselines:
+
+1. the generated historical baseline query is evaluated before live startup
+2. the result bindings are materialized into named-graph static quads
+3. those quads are injected into the live RSP engine before `start_processing()`
+4. the live query starts only after that injection succeeds
+
 ## What Janus Stores
 
 Janus does not retain all historical events or all historical sliding-window outputs as permanent runtime state.
@@ -105,24 +184,22 @@ It does not retain:
 - all sliding-window result batches after bootstrap
 - a continuously merged historical/live relation
 
-## Anchor Selection
-
-Baseline values are materialized per anchor subject.
-
-The current implementation prefers binding variables named:
+For query-defined baselines it retains:
 
-- `sensor`
-- `subject`
-- `entity`
-- `s`
+- the evaluated historical bindings per baseline name
+- the final materialized baseline quads inside the live static store
 
-If none of those exist, Janus falls back to the first IRI-like binding it can find.
+## Limitations
 
-This means historical baseline queries work best when they explicitly return a stable anchor variable such as `?sensor`.
+- query-defined baselines are startup snapshots, not continuously updated historical/live state
+- the `GRAPH` template predicates must be concrete IRIs
+- template variables must be projected by the baseline query
+- template subjects must resolve to an IRI or blank node
+- large baseline result sets can make static-store injection expensive at startup
 
 ## Recommended Usage
 
 - Prefer fixed historical windows first.
 - Use historical sliding windows only when you need a baseline derived from multiple historical subwindows.
 - Keep baseline queries compact, ideally one row per anchor.
-- Start with baseline values such as `mean` and `sigma`; add `slope` or quantiles later if needed.
+- Start with compact baseline values such as `mean`, `sigma`, or `dayAvgValue`; add more only when needed.
diff --git a/docs/BENCHMARKING.md b/docs/BENCHMARKING.md
new file mode 100644
index 0000000..9bf914b
--- /dev/null
+++ b/docs/BENCHMARKING.md
@@ -0,0 +1,119 @@
+# Benchmarking
+
+This document defines the current benchmark harness for Janus backend work.
+
+## Goals
+
+The benchmark suite is split by engine path so regressions are easier to localize:
+
+- `storage_write`: ingest-only storage throughput
+- `historical_fixed`: fixed historical window execution
+- `historical_sliding`: sliding historical window execution
+- `live_injection`: live event ingestion to first emitted result
+- `hybrid_baseline`: live window plus static baseline join
+- `janusql_e2e`: HTTP/WebSocket Janus-QL first-result latency for historical queries
+- `janusql_live_mqtt_e2e`: HTTP/WebSocket Janus-QL first-result latency for broker-backed live and hybrid queries
+
+These benchmarks are intended for backend performance work on the current repository state.
+They are not a substitute for a public performance report.
+
+## Run Commands
+
+`cargo bench` already uses Cargo's optimized `bench` profile, so there is no extra `--release`
+flag to pass here:
+
+```bash
+cargo bench --bench storage_write
+cargo bench --bench historical_fixed
+cargo bench --bench historical_sliding
+cargo bench --bench live_injection
+cargo bench --bench hybrid_baseline
+cargo bench --bench janusql_e2e
+cargo bench --bench janusql_live_mqtt_e2e
+```
+
+To verify that all benchmark targets compile without running them:
+
+```bash
+cargo bench --no-run
+```
+
+## What Each Benchmark Measures
+
+### `storage_write`
+
+Measures `StreamingSegmentedStorage::write_rdf_event` throughput on fresh storage with large flush
+thresholds so the benchmark isolates write-path cost rather than background flush cost.
+
+### `historical_fixed`
+
+Measures a single fixed historical window query over deterministic stored events in `ex:graph1`.
+
+### `historical_sliding`
+
+Measures a sliding historical window scan over deterministic stored events placed in a recent time
+range so the windows stay valid relative to the executor's wall-clock based offset logic.
+
+### `live_injection`
+
+Measures the live path from event injection into `LiveStreamProcessing` to the first emitted
+result. The harness injects a sentinel event at the end to close remaining windows deterministically.
+
+### `hybrid_baseline`
+
+Measures a hybrid-style query where live window bindings join against static baseline data already
+materialized into the live engine. This isolates hybrid join cost without requiring an MQTT broker
+or the HTTP server.
+
+### `janusql_e2e`
+
+Measures end-to-end Janus-QL latency through the HTTP API:
+
+- `historical_preloaded`: register query, start query, subscribe over WebSocket, wait for first result
+- `historical_via_replay`: start replay, register query, start query, subscribe over WebSocket, wait for first result
+
+This target currently covers historical Janus-QL end-to-end flows. Full live or hybrid HTTP e2e
+benchmarks are covered separately in `janusql_live_mqtt_e2e`, because Janus live execution is
+broker-driven at the API layer.
+
+### `janusql_live_mqtt_e2e`
+
+Measures broker-backed Janus-QL latency through the HTTP API and WebSocket result stream:
+
+- `mqtt_live_first_result`: register a live query, start it, subscribe over WebSocket, publish MQTT events, wait for the first live result
+- `mqtt_hybrid_first_result`: register a hybrid query with historical baseline bootstrap, start it, wait for baseline warm-up, subscribe over WebSocket, publish MQTT events, wait for the first live result
+
+This target requires an MQTT broker reachable from the benchmark process. By default it uses
+`127.0.0.1:1883` and topic `sensors`, and it can be overridden with:
+
+- `JANUS_BENCH_MQTT_HOST`
+- `JANUS_BENCH_MQTT_PORT`
+- `JANUS_BENCH_MQTT_TOPIC`
+- `JANUS_BENCH_MQTT_STREAM_URI`
+
+## Reproducibility Rules
+
+When comparing numbers across commits:
+
+1. Run on a quiet machine.
+2. Use the same hardware, Rust toolchain, and bench profile.
+3. Avoid running multiple benchmark targets in parallel.
+4. Capture the exact command, branch, and commit SHA with the results.
+5. Record CPU model, RAM, OS version, and whether the system was thermally constrained.
+
+## Recommended Workflow
+
+For routine optimization work:
+
+```bash
+cargo bench --no-run
+cargo bench --bench storage_write
+cargo bench --bench historical_fixed
+cargo bench --bench historical_sliding
+cargo bench --bench live_injection
+cargo bench --bench hybrid_baseline
+cargo bench --bench janusql_e2e
+cargo bench --bench janusql_live_mqtt_e2e
+```
+
+For benchmark result reviews, attach the Criterion output directory from `target/criterion/`.
diff --git a/docs/BENCHMARK_RESULTS.md b/docs/BENCHMARK_RESULTS.md
index d9a7cb6..1c623b5 100644
--- a/docs/BENCHMARK_RESULTS.md
+++ b/docs/BENCHMARK_RESULTS.md
@@ -119,20 +119,19 @@ For benchmark reproducibility, document:
 
 ## Running Benchmarks
 
-To reproduce these results:
+To run the current benchmark harness:
 
 ```bash
-# Write performance
-cargo bench --bench write_benchmark --release
-
-# Read performance
-cargo bench --bench benchmark --release
-
-# Point query performance
-cargo bench --bench benchmark --release
+cargo bench --bench storage_write
+cargo bench --bench historical_fixed
+cargo bench --bench historical_sliding
+cargo bench --bench live_injection
+cargo bench --bench hybrid_baseline
+cargo bench --bench janusql_e2e
+cargo bench --bench janusql_live_mqtt_e2e
 ```
 
-For detailed testing instructions, see [WRITING_BENCHMARKS.md](./WRITING_BENCHMARKS.md).
+For detailed testing instructions, see [BENCHMARKING.md](./BENCHMARKING.md).
 
 ## Historical Results
 
@@ -145,11 +144,11 @@ This section will track benchmark results across releases:
 
 When adding new benchmark results:
 
-1. Use release build: `--release`
+1. Use `cargo bench` so the optimized bench profile is active
 2. Run on quiet system (minimal background load)
 3. Include dataset size and query pattern
 4. Document hardware configuration
 5. Report mean and variance
 6. Submit results via PR with hardware details
 
-See [WRITING_BENCHMARKS.md](./WRITING_BENCHMARKS.md) for comprehensive benchmark testing guide.
+See [BENCHMARKING.md](./BENCHMARKING.md) for the current benchmark guide.
diff --git a/docs/HTTP_API.md b/docs/HTTP_API.md
index 55f892d..53f27d4 100644
--- a/docs/HTTP_API.md
+++ b/docs/HTTP_API.md
@@ -61,7 +61,7 @@ Register a new JanusQL query.
 ```json
 {
   "query_id": "sensor_query_1",
-  "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }"
+  "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }"
 }
 ```
 
@@ -398,7 +398,7 @@ curl -X POST http://localhost:8080/api/queries \
   -H "Content-Type: application/json" \
   -d '{
     "query_id": "temp_query",
-    "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }"
+    "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }"
   }'
 ```
 
@@ -462,7 +462,7 @@ response = requests.post(
     f"{BASE_URL}/api/queries",
     json={
         "query_id": "my_query",
-        "janusql": "PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600] WHERE { WINDOW ex:histWindow { ?s ?p ?o . } }"
+        "janusql": "PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:histWindow { ?s ?p ?o . } }"
     }
 )
 print(f"Register: {response.json()}")
@@ -500,7 +500,7 @@ async function demo() {
   // Register a query
   const registerResponse = await axios.post(`${BASE_URL}/api/queries`, {
     query_id: 'js_query',
-    janusql: 'PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600] WHERE { WINDOW ex:histWindow { ?s ?p ?o . } }'
+    janusql: 'PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:histWindow { ?s ?p ?o . } }'
   });
   console.log('Registered:', registerResponse.data);
 
@@ -629,7 +629,7 @@ For a simple demo dashboard with "Start Replay" and "Start Query" buttons:
           headers: { 'Content-Type': 'application/json' },
           body: JSON.stringify({
             query_id: QUERY_ID,
-            janusql: 'PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }'
+            janusql: 'PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:histWindow { ?sensor ex:temperature ?temp . } }'
           })
         });
 
diff --git a/docs/JANUSQL.md b/docs/JANUSQL.md
index 9ec1a6d..fdc2a4a 100644
--- a/docs/JANUSQL.md
+++ b/docs/JANUSQL.md
@@ -10,6 +10,7 @@ A Janus-QL query typically contains:
 - a `REGISTER` clause
 - one or more `FROM NAMED WINDOW` clauses
 - an optional `USING BASELINE` clause
+- optional `DEFINE BASELINE ... ON WINDOW ... AS SELECT ...` clauses
 - a `WHERE` clause with `WINDOW <name> { ... }` blocks
 
 Example:
@@ -92,21 +93,90 @@ Semantics:
 
 If the clause is absent, the HTTP/API registration-level `baseline_mode` is used as a fallback.
 
+## Query-Defined Baselines
+
+Janus also supports query-defined baselines. They are evaluated over a historical `LOG` window before live startup, materialized through a `GRAPH :name { ... }` template, and injected into the live RSP engine as static RDF quads.
+
+Canonical example:
+
+```sparql
+PREFIX : <http://example.org/>
+
+FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60000 STEP 1000]
+FROM NAMED WINDOW :historyDay ON LOG :stream [START 0 END 86400000]
+
+DEFINE BASELINE :dayBaseline ON WINDOW :historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor :hasValue ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream :output AS
+USING BASELINE :dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {
+  WINDOW :liveMinute {
+    ?sensor :hasValue ?value .
+  }
+
+  GRAPH :dayBaseline {
+    ?sensor :dayAvgValue ?dayAvgValue .
+  }
+}
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
+```
+
+Semantics:
+
+- `DEFINE BASELINE :dayBaseline ON WINDOW :historyDay AS SELECT ...` defines the historical binding relation that is prepared at startup.
+- `USING BASELINE :dayBaseline` marks that baseline as required and injects it into the live engine before live processing begins.
+- `GRAPH :dayBaseline { ... }` is the materialization template. Janus substitutes each baseline row into that template and emits the resulting quads into the live static store.
+- baseline variables such as `?dayAvgValue` are then available to the live query in `SELECT`, `GROUP BY`, `HAVING`, and arithmetic expressions.
+
+## Query-Defined Baseline Materialization
+
+Materialization is template-driven rather than inferred from `SELECT` aliases:
+
+- the `GRAPH :baselineName { ... }` block defines the RDF shape that is inserted
+- the baseline query must project every variable used by that template
+- template predicates must be concrete IRIs
+- template subjects must resolve to an IRI or blank node
+
+Example binding:
+
+- `?sensor = :s1`
+- `?dayAvgValue = 42.0`
+
+becomes:
+
+```trig
+GRAPH :dayBaseline {
+  :s1 :dayAvgValue 42.0 .
+}
+```
+
 ## What Janus Generates Internally
 
 The parser splits the query into:
 
 - one live RSP-QL query built from live windows
 - one SPARQL query per historical window
+- one SPARQL query per query-defined baseline
 
 Important detail:
 
 - non-window patterns in the `WHERE` clause are preserved in the live query
-- this is what makes baseline joins like `?sensor baseline:mean ?mean` work during live execution
+- this is what makes static joins such as `GRAPH :dayBaseline { ?sensor :dayAvgValue ?dayAvgValue . }` work during live execution
 
 ## Baseline Predicates
 
-Baseline values are exposed to the live side as static triples under:
+Legacy `USING BASELINE <window> LAST|AGGREGATE` values are exposed to the live side as static triples under:
 
 ```text
 https://janus.rs/baseline#<variable_name>
@@ -125,6 +195,24 @@ ex:s1  <https://janus.rs/baseline#mean>  "21.5"
 
 This is why live queries join on `baseline:*` predicates rather than directly reusing historical bindings.
 
+Query-defined baselines use the baseline name as the graph IRI instead:
+
+```trig
+GRAPH :dayBaseline {
+  :s1 :dayAvgValue 42.0 .
+}
+```
+
+The live query must therefore join through `GRAPH :dayBaseline { ... }` rather than through `baseline:*` predicates.
+
+## Limitations
+
+- query-defined baseline materialization is a startup snapshot, not a continuously updated historical/live relation
+- the `GRAPH` template predicates must be concrete IRIs
+- template variables must be projected by the baseline query
+- template subjects must resolve to an IRI or blank node
+- large baseline result sets may make static-store injection expensive at startup
+
 ## Practical Guidance
 
 - Use fixed historical windows when you want one clean baseline snapshot.
diff --git a/docs/PAPER_BENCHMARKING.md b/docs/PAPER_BENCHMARKING.md
new file mode 100644
index 0000000..fe6fa36
--- /dev/null
+++ b/docs/PAPER_BENCHMARKING.md
@@ -0,0 +1,430 @@
+# Paper Benchmarking
+
+This document defines the paper-facing benchmark harnesses for the two current Janus hypotheses:
+
+- H1.1: unified Janus hybrid execution versus a decomposed Oxigraph-based baseline
+- H2: historical and hybrid query latency scaling with dataset size
+
+The comparison is intentionally limited to:
+
+1. `janus_unified`
+2. `decomposed_oxigraph`
+
+No Apache Jena or SPARQL-ST path is included in this harness version.
+
+## Purpose
+
+These harnesses are not Criterion microbenchmarks. They are paper-oriented runners that emit:
+
+- raw JSONL with one row per recorded run
+- summary CSV designed for paper tables
+- a scaling-fit CSV for H2
+- reproducibility metadata on every raw row
+
+Default output roots:
+
+- `target/paper_benchmarks/paper_hybrid_coordination`
+- `target/paper_benchmarks/paper_historical_scaling`
+
+## Warmup Behavior
+
+Both binaries support:
+
+- `--warmup-runs N`
+- `--include-warmups`
+
+Warmup runs execute the same workload as measured runs.
+
+Default behavior:
+
+- warmups are executed
+- warmups are excluded from the emitted JSONL and summary CSV files
+
+If `--include-warmups` is set, warmup rows are written with `is_warmup: true`.
+
+## Cold Vs Warm Mode
+
+Both binaries support:
+
+- `--mode cold|warm`
+
+Default mode:
+
+- `warm`
+
+### H1.1 `paper_hybrid_coordination`
+
+`warm` mode:
+
+- reuses a prebuilt historical workload in memory
+- reuses pre-generated live events
+- still initializes a fresh live engine per run
+- measures query execution, baseline retrieval/materialization, live publication, and first-result latency
+
+`cold` mode:
+
+- rebuilds historical storage and workload data per run
+- rebuilds live event inputs per run
+- includes workload/store setup cost in end-to-end latency
+
+### H2 `paper_historical_scaling`
+
+`warm` mode:
+
+- reuses a pre-generated historical dataset per dataset size
+- measures query execution path on an already initialized dataset
+
+`cold` mode:
+
+- regenerates and reloads the dataset per run
+- includes dataset/store setup cost in latency
+
+## Measured Vs Estimated Metrics
+
+The harness distinguishes direct timing/size observations from logical or derived values.
+
+### H1.1 Raw Metrics
+
+Directly recorded timestamps:
+
+- `client_start`
+- `query_registered`
+- `historical_start`
+- `historical_done`
+- `live_ready`
+- `first_event_published`
+- `first_result_engine`
+- `first_result_client`
+
+Directly derived from timestamps:
+
+- `e2e_latency_ms = first_result_client - client_start`
+
+Estimated fields:
+
+- `estimated_useful_engine_work_ms`
+  - Janus unified: `(historical_done - historical_start) + (first_result_engine - first_event_published)`
+  - decomposed Oxigraph: same formula, where the historical term is external Oxigraph historical work and the live term is Janus live processing until the joined result is available
+- `estimated_coordination_overhead_ms = e2e_latency_ms - estimated_useful_engine_work_ms`
+- `estimated_external_transfer_bytes`
+  - logical serialized size of intermediate payloads exchanged between decomposed components
+
+Measured byte payload sizes:
+
+- `historical_intermediate_bytes`
+- `live_intermediate_bytes`
+- `final_result_bytes`
+
+Structural counts:
+
+- `components`
+- `process_boundaries`
+- `serialization_steps`
+
+Result correctness:
+
+- `result_count`
+- `result_hash`
+- `equivalent_to_baseline`
+
+### H2 Raw Metrics
+
+Directly measured or observed:
+
+- `latency_ms`
+- `result_count`
+- `peak_rss_mb` when available
+
+Logical or derived:
+
+- `logical_quads_scanned`
+  - number of quads logically covered by the requested time range, not a low-level physical storage scan count
+- `selectivity = result_count / dataset_size_quads`
+- `throughput_quads_per_sec = logical_quads_scanned / latency`
+
+Result correctness:
+
+- `result_hash`
+
+## H1.1 Hybrid Query Semantics
+
+The H1.1 benchmark validates unified versus decomposed hybrid execution. The query model integrates three distinct elements:
+- Historical component: Executes a query over historical events stored in a segmented storage backend (using a SPARQL engine to retrieve baseline bindings).
+- Live stream/window component: Processes real-time events through a sliding window stream operator ([RANGE 10000 STEP 1000]).
+- Hybrid result: Merges the live stream window output with the materialized historical baseline statements matching on the join key (sensor).
+
+### Execution Architectures
+
+#### Janus-QL Unified Execution
+Janus-QL compiles the historical and live stream elements into a single execution graph. The historical sub-query is executed once, and its results are materialized as internal static bindings. As live events stream into the engine, they are joined inline with the static bindings within the same process. No serialization or IPC boundaries are crossed to merge live stream and historical data.
+
+#### Decomposed Baseline
+The decomposed baseline, labeled "Oxigraph historical + Janus live window processor + external join", coordinates execution across separate stages:
+1. Oxigraph historical query: An external Oxigraph engine queries the historical dataset to retrieve the baseline bindings. These are returned and materialized into memory in the client coordinate space.
+2. Janus live window processor: A separate instance of the Janus live processing engine executes a live-only RSP-QL query over the live events stream.
+3. External join/materialization: The client coordinate space collects the intermediate live window results and performs an external hash join against the materialized historical bindings on the matching sensor variable.
+
+### Equivalence Target
+The primary target for correctness equivalence checking is the final hybrid result (hybrid_result_hash and hybrid_result_count). Historical equivalence is monitored as diagnostic evidence, whereas live-only intermediate equivalence is not directly applicable during benchmark execution because Janus Unified does not produce a separate intermediate live result.
+
+## Result Equivalence Checking
+
+Each run emits `result_hash`, computed as a deterministic SHA-256 hash over canonicalized result rows:
+
+- row keys sorted lexicographically
+- normalized string values
+- canonical rows serialized before hashing
+
+For H1.1:
+
+- `janus_unified` is compared against `decomposed_oxigraph` for the same run workload
+- `equivalent_to_baseline` is set on the Janus row
+- the decomposed baseline row uses `equivalent_to_baseline: null`
+
+For H2:
+
+- no baseline equivalence field is emitted because H2 is a scaling study across query classes, not a paired-system comparison
+
+## H1.1 Command
+
+```bash
+cargo run --release --bin paper_hybrid_coordination -- \
+  --warmup-runs 1 \
+  --runs 10 \
+  --historical-events 10000 \
+  --live-events 32 \
+  --mode warm
+```
+
+Outputs:
+
+- `paper_hybrid_coordination.raw.jsonl`
+- `paper_hybrid_coordination.summary.csv`
+
+## H1.2 Sustained Hybrid Window Execution
+
+The H1.2 benchmark evaluates sustained hybrid query execution performance over repeated sliding windows. It supports both deterministic virtual event-time replay and slower wall-clock replay.
+
+While H1.1 focuses on the latency of registering and obtaining the very first hybrid query result (coordination overhead check), H1.2 models a continuous stream processor running over a logical stream duration (by default 180 or 240 logical seconds).
+
+### Execution Semantics
+
+- Virtual Event-Time Ingestion (`--time-mode virtual`, default): Events are published back-to-back in virtual time rather than sleeping in wall-clock time. The live stream engine's sliding window boundaries are advanced entirely by the event timestamps. This is the deterministic, high-repeat mode and is the correct default for engine-overhead measurement.
+- Wall-Clock Replay (`--time-mode wall-clock`): Events are published according to real elapsed time. `event_rate_hz` determines the target spacing between events, so `event_rate_hz=4` means one event every 250 ms. Event timestamps still follow the logical schedule; only the publication timing changes. This mode is intended as a realism and sanity check for user-observed result timing, not as the main repeated performance matrix.
+- Watermark/Flush Behavior: To reliably finalize and evaluate the final window, a watermark sentinel event is published at the end of the stream (offset by +20 seconds past the logical duration bounds), forcing all remaining active windows to close and emit their results.
+- Wall-Clock Sentinel Timing: In wall-clock mode, the harness schedules normal events against a monotonic `Instant` and sends the sentinel only after the logical live duration has elapsed. This keeps replay duration approximately aligned with `logical_live_duration_seconds * 1000`, plus processing and synchronization overhead.
+- Decomposed Baseline coordination: For each completed window, the decomposed baseline performs:
+  1. Oxigraph historical retrieval (once).
+  2. Janus live window processor execution (returns a live stream result for each slide).
+  3. Client coordinate join (combining the window's live result and the materialized historical bindings).
+  These stages are measured slide-by-slide to determine the per-window hybrid latency.
+
+### Latency Interpretation
+
+- Processing latency: CPU/runtime cost after data and window readiness. In H1.2 this remains `first_hybrid_result_latency_ms` and the per-window hybrid latency fields.
+- Wall-clock result offset: When a user would actually observe a result since replay start. In wall-clock mode this is reported via `first_hybrid_result_wall_clock_ms` and per-window `window_result_wall_clock_offsets_ms`, with paper-facing summaries using the in-horizon p50/p95 offset fields.
+
+Virtual mode is still the recommended mode for final repeated measurements because it is fast, deterministic, and isolates engine/runtime overhead. Wall-clock mode is slower and more sensitive to OS scheduling jitter, so use it as a realism/sanity benchmark.
+
+### Window Horizon Filtering and Sentinel Flushes
+
+For logical_live_duration_seconds=240, window_size_seconds=120, and window_slide_seconds=60:
+- The virtual event-time stream starts at 1900000000000 ms (relative 0 seconds) and ends at 1900000239000 ms (relative 239 seconds).
+- The first completed window triggers at 59 seconds offset (ending at 179 seconds), and the second triggers at 119 seconds offset (ending at 239 seconds). Both end before or at the 240 seconds horizon, meaning they contain only normal stream events.
+- The third window (ending at 299 seconds) and fourth window (ending at 359 seconds) extend past the 240 seconds logical duration. These are only completed and emitted because the close_stream call publishes a sentinel watermark at 259 seconds, forcing a flush of all active windows.
+- To prevent sentinel-finalized flush windows or other out-of-horizon windows from skewing summary statistics, the harness separates completed windows:
+  - completed_windows_total: The total count of all windows emitted (4).
+  - completed_windows_in_horizon: The count of windows ending within the logical duration (2).
+  - flush_windows: The count of windows finalized only by the sentinel flush (2).
+- Latency, equivalence, result count, and transfer byte statistics are computed exclusively over completed_windows_in_horizon.
+
+## H1.2 Command
+
+```bash
+cargo run --release --bin paper_sustained_hybrid -- \
+  --warmup-runs 1 \
+  --runs 5 \
+  --historical-events 10000 \
+  --live-duration-seconds 240 \
+  --event-rate-hz 1 \
+  --window-size-seconds 120 \
+  --window-slide-seconds 60 \
+  --mode warm \
+  --time-mode virtual
+```
+
+Outputs:
+
+- `paper_sustained_hybrid.raw.jsonl`
+- `paper_sustained_hybrid.summary.csv`
+
+Recommended wall-clock sanity check:
+
+```bash
+cargo run --release --bin paper_sustained_hybrid -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 1000 \
+  --live-duration-seconds 20 \
+  --event-rate-hz 4 \
+  --window-size-seconds 10 \
+  --window-slide-seconds 5 \
+  --mode warm \
+  --time-mode wall-clock \
+  --debug-equivalence \
+  --output-dir target/paper_benchmarks/pre_final_h1_2_wall_clock_short
+```
+
+Optional longer paper sanity check:
+
+```bash
+cargo run --release --bin paper_sustained_hybrid -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 10000 \
+  --live-duration-seconds 180 \
+  --event-rate-hz 4 \
+  --window-size-seconds 120 \
+  --window-slide-seconds 60 \
+  --mode warm \
+  --time-mode wall-clock \
+  --debug-equivalence \
+  --output-dir target/paper_benchmarks/h1_2_wall_clock_180s_4hz
+```
+
+## H2 Command
+
+```bash
+cargo run --release --bin paper_historical_scaling -- \
+  --warmup-runs 1 \
+  --runs 5 \
+  --dataset-sizes 100000,500000,1000000,5000000 \
+  --mode warm
+```
+
+Outputs:
+
+- `paper_historical_scaling.raw.jsonl`
+- `paper_historical_scaling.summary.csv`
+- `paper_historical_scaling.fit.csv`
+
+## H2 Scaling Fit
+
+For each `query_type`, the harness computes a simple linear model:
+
+```text
+latency_ms = intercept + slope * dataset_size_quads
+```
+
+Reported columns:
+
+- `query_type`
+- `mode`
+- `slope_ms_per_100k_quads`
+- `intercept_ms`
+- `r_squared`
+- `number_of_points`
+
+This CSV is the operational check for “scales predictably.”
+
+## Validation Commands
+
+Recommended correctness and build validation:
+
+```bash
+cargo fmt
+cargo clippy --all-targets --all-features -- -D warnings
+cargo test --all-features
+cargo bench --no-run
+```
+
+Recommended smoke validation:
+
+```bash
+cargo run --release --bin paper_hybrid_coordination -- \
+  --warmup-runs 1 --runs 2 --historical-events 1000 --live-events 8 --mode warm \
+  --output-dir target/paper_benchmarks/validation_h1
+
+cargo run --release --bin paper_historical_scaling -- \
+  --warmup-runs 1 --runs 2 --dataset-sizes 10000,50000,100000 --mode warm \
+  --output-dir target/paper_benchmarks/validation_h2
+```
+
+## Query-Defined Baseline Smoke Benchmark
+
+This runner exercises the query-defined baseline path with a short, deterministic fixture:
+
+- historical baseline query execution is always accelerated
+- GRAPH-template materialization
+- static quad injection
+- live startup
+- first-result latency
+- live-only comparison with the same live window and aggregate
+- live replay can run in accelerated mode, which remains the default, or realtime mode for wall-clock sanity checks
+
+Binary:
+
+- `paper_query_defined_baseline`
+
+Default smoke command:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 0 --runs 1
+```
+
+Live replay controls:
+
+- `--live-replay-mode accelerated|realtime`
+- `--live-rate-hz <float>`
+- `--live-duration-seconds <u64>`
+- `--live-window-size-seconds <u64>`
+- `--live-window-slide-seconds <u64>`
+
+Behavior notes:
+
+- historical preload and historical baseline evaluation always stay accelerated
+- accelerated live replay preserves the current benchmark behavior and does not add sleeps
+- realtime live replay sleeps only between live events, so it is suitable for short live-arrival sanity checks
+- the realtime path is not intended for million-scale historical experiments; keep live replay accelerated unless you are explicitly testing wall-clock behavior
+- when realtime mode is selected without explicit window values, the runner uses a 240-second live duration with 120-second windows sliding every 60 seconds
+
+The runner writes a timestamped directory under `logs/benchmark/query_defined_baseline/` containing:
+
+- `query_defined_baseline.raw.json`
+- `query_defined_baseline.summary.csv`
+- `query_defined_baseline_results.md`
+
+Longer run after smoke passes:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 1 --runs 25
+```
+
+Note:
+
+- the smoke fixture keeps the historical window fixed so the default run stays short and deterministic
+- the smoke runner uses the tested `ex:` alias surface and a conservative live query shape so it stays within the current runtime parse path
+- if you want to stretch the benchmark, increase `--runs` first before expanding the fixture size
+- the benchmark verifies `?sensor`, `?minuteAvgValue`, `?dayAvgValue`, and `?difference` on the baseline path and compares against a live-only query with the same live window
+- realtime mode records `expected_emitted_windows`, `expected_full_windows`, `warmup_window_count`, observed emitted-window counts, observed row counts, and per-window latency values when available
+- realtime mode may emit an initial partial or warm-up window on the first slide, depending on engine boundary semantics
+
+## Recommended Final Paper Commands
+
+```bash
+cargo run --release --bin paper_hybrid_coordination -- \
+  --warmup-runs 1 --runs 10 --historical-events 10000 --live-events 32 --mode warm \
+  --output-dir target/paper_benchmarks/paper_h1_final
+
+cargo run --release --bin paper_historical_scaling -- \
+  --warmup-runs 1 --runs 5 --dataset-sizes 100000,500000,1000000,5000000 --mode warm \
+  --output-dir target/paper_benchmarks/paper_h2_final
+```
+
+For final numbers:
+
+1. run on a quiet machine
+2. keep the emitted raw JSONL with the paper tables
+3. retain commit SHA, branch, OS, CPU, RAM, and exact command line
diff --git a/docs/PAPER_BENCHMARK_RESULTS_TEMPLATE.md b/docs/PAPER_BENCHMARK_RESULTS_TEMPLATE.md
new file mode 100644
index 0000000..cfa4c07
--- /dev/null
+++ b/docs/PAPER_BENCHMARK_RESULTS_TEMPLATE.md
@@ -0,0 +1,73 @@
+# Paper Benchmark Results Template
+
+## H1.1 Hybrid Query Performance
+
+| System | Mode | Historical Latency (ms) | Live Stream Processing Latency (ms) | External Join Latency (ms) | First Hybrid Result Latency (ms) | External Transfer Bytes | Historical Equivalence | Hybrid Equivalence |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| Janus unified | warm | | | | | | | |
+| Oxigraph historical + Janus live window processor + external join | warm | | | | | | | |
+
+## H1.2 Sustained Hybrid Query Performance
+
+| System | Mode | Time Mode | Runs | Logical Live Duration (s) | Event Rate (Hz) | Event Interval (ms) | Window Size (ms) | Window Slide (ms) | Completed Windows Total | Completed Windows In Horizon | Flush Windows | Missed Windows | Historical Prep Latency (ms) | P50 Window Hybrid Latency (ms) | P95 Window Hybrid Latency (ms) | P50 Window Result Wall Clock Offset (ms) | P95 Window Result Wall Clock Offset (ms) | Avg External Join Latency (ms) | Avg External Transfer Bytes / Window | Equivalence Rate | Avg Wall Clock Duration (ms) | Uses Virtual Event Time |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| Janus unified | warm | virtual | | | | | | | | | | | | | | | | | | | | |
+| Oxigraph historical + Janus live window processor + external join | warm | virtual | | | | | | | | | | | | | | | | | | | | |
+
+Paper-facing H1.2 latency, transfer, and equivalence metrics are computed over completed windows in horizon only. Flush windows are tracked separately and excluded from those summaries.
+
+## H1.2b Wall-Clock Sanity Check
+
+| System | Mode | Time Mode | Live Duration (s) | Event Rate (Hz) | Window Size (s) | Window Slide (s) | Completed Windows Total | Completed Windows In Horizon | Flush Windows | First Hybrid Result Wall Clock (ms) | P50 Window Result Wall Clock Offset (ms) | P95 Window Result Wall Clock Offset (ms) | Avg Wall Clock Duration (ms) | Avg Wall Clock Overhead (ms) | Equivalence Rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| Janus unified | warm | wall-clock | | | | | | | | | | | | | |
+| Oxigraph historical + Janus live window processor + external join | warm | wall-clock | | | | | | | | | | | | | |
+
+
+## H2 Historical Scaling Result
+
+Lead with simple latency values, not slope/R². Use `p50_latency_ms` as the main number.
+
+If the selected H2 output directory does not include `5,000,000` quads, label the table as validation-only and replace the size columns with the available dataset sizes.
+
+## H2 Simple Latency Table
+
+| query_type | latency_100k_ms | latency_500k_ms | latency_1m_ms | latency_5m_ms | simple_takeaway |
+| --- | --- | --- | --- | --- | --- |
+| point_lookup |  |  |  |  | flat |
+| fixed_window |  |  |  |  | almost flat |
+| proportional_range_10 |  |  |  |  | grows moderately |
+| proportional_range_50 |  |  |  |  | grows strongly |
+| full_range |  |  |  |  | largest scan cost |
+| hybrid_baseline_lookup |  |  |  |  | largest scan cost |
+
+## H2 Optional Latency Growth Table
+
+| query_type | latency_increase_from_smallest_to_largest_ms | multiplier_from_smallest_to_largest | simple_interpretation |
+| --- | --- | --- | --- |
+| point_lookup |  |  | Point lookup barely changes |
+| fixed_window |  |  | Fixed-window query stays nearly flat |
+| proportional_range_10 |  |  | 10% range grows moderately as it scans more data |
+| proportional_range_50 |  |  | 50% range grows strongly as it scans more data |
+| full_range |  |  | Full range grows because it scans more data |
+| hybrid_baseline_lookup |  |  | Hybrid baseline follows full-range scan behavior |
+
+## H2 Plot
+
+Reference:
+
+- `target/paper_benchmarks/h2_latency_scaling.png`
+- `target/paper_benchmarks/h2_latency_scaling_logy.png` when the flatter query lines are hard to read on a linear y-axis
+
+## H2 Scaling Fit Appendix
+
+Retain the fit output as appendix/internal support, not the primary result.
+
+| Query Type | Mode | Slope (ms / 100k quads) | Intercept (ms) | R² | Number Of Points |
+| --- | --- | --- | --- | --- | --- |
+| point_lookup | warm |  |  |  |  |
+| fixed_window | warm |  |  |  |  |
+| proportional_range_10 | warm |  |  |  |  |
+| proportional_range_50 | warm |  |  |  |  |
+| full_range | warm |  |  |  |  |
+| hybrid_baseline_lookup | warm |  |  |  |  |
diff --git a/docs/QUERY_BASELINE_BENCHMARK.md b/docs/QUERY_BASELINE_BENCHMARK.md
new file mode 100644
index 0000000..d0995b0
--- /dev/null
+++ b/docs/QUERY_BASELINE_BENCHMARK.md
@@ -0,0 +1,482 @@
+# Query-Defined Baseline Benchmark
+
+This document explains how to run the Janus query-defined baseline benchmark used for the paper experiments.
+
+The benchmark evaluates Janus-QL queries of the following form:
+
+```sparql
+DEFINE BASELINE :dayBaseline ON WINDOW :historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor :hasValue ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream :output AS
+USING BASELINE :dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {
+  WINDOW :liveMinute {
+    ?sensor :hasValue ?value .
+  }
+
+  GRAPH :dayBaseline {
+    ?sensor :dayAvgValue ?dayAvgValue .
+  }
+}
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
+```
+
+The benchmark measures the cost of:
+
+1. generating and storing historical events,
+2. evaluating the historical `DEFINE BASELINE` query,
+3. materializing baseline bindings into a static named graph,
+4. injecting the static graph into the live RSP engine,
+5. executing the live query with a `GRAPH :baselineName { ... }` join,
+6. validating correctness,
+7. recording CPU and memory usage.
+
+## Benchmark modes
+
+The benchmark supports two live replay modes:
+
+### Accelerated mode
+
+This is the default mode.
+
+Historical and live events use deterministic timestamps, but live events are submitted as fast as possible. This is useful for scalability experiments because it avoids waiting in wall-clock time.
+
+Use this mode for million-scale experiments.
+
+### Realtime mode
+
+In realtime mode, historical data is still generated and loaded as fast as possible, but live events are replayed with wall-clock sleeps according to the configured live rate.
+
+This mode is intended only for short live-arrival sanity checks.
+
+For example, with:
+
+```text
+live rate = 4 Hz
+duration = 240 seconds
+window size = 120 seconds
+window slide = 60 seconds
+```
+
+the benchmark emits:
+
+```text
+live events = 4 × 240 = 960
+expected emitted windows = 4
+expected full windows = 3
+warm-up windows = 1
+```
+
+The first emitted window is a warm-up window at the first slide boundary.
+
+## Requirements
+
+Recommended server configuration:
+
+```text
+CPU: 4 cores or more
+RAM: 16 GB minimum, 32 GB preferred
+Disk: local SSD preferred
+OS: Linux recommended
+Rust: stable toolchain
+```
+
+The 10M historical-event experiment may use several GB of memory. In previous runs, the 10M configuration peaked around 5 GB RSS.
+
+## Build and test
+
+From the Janus repository root:
+
+```bash
+cargo build --release
+cargo test -- --nocapture
+```
+
+## Smoke test
+
+Always run a small smoke benchmark first:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 10K \
+  --baseline-entities 10
+```
+
+The output should look like:
+
+```text
+benchmark=query_defined_baseline
+correctness_passed=true
+warmup_runs=0 measured_runs=1
+output_dir=logs/benchmark/query_defined_baseline/<timestamp>
+raw_json=logs/benchmark/query_defined_baseline/<timestamp>/query_defined_baseline.raw.json
+summary_csv=logs/benchmark/query_defined_baseline/<timestamp>/query_defined_baseline.summary.csv
+markdown=logs/benchmark/query_defined_baseline/<timestamp>/query_defined_baseline_results.md
+```
+
+## Experiment A: historical-size scaling
+
+This experiment fixes the baseline relation size and varies the historical log size.
+
+It answers:
+
+```text
+How does query-defined baseline evaluation scale as the historical log grows?
+```
+
+Run:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 1 \
+  --runs 3 \
+  --historical-events 1M,5M,10M \
+  --baseline-entities 10
+```
+
+Expected interpretation:
+
+```text
+Historical baseline evaluation should dominate runtime.
+GRAPH-template materialization and static graph injection should remain small because the baseline relation has only 10 rows.
+```
+
+Important metrics:
+
+```text
+historical_events
+baseline_entities
+correctness_rate
+baseline_eval_ms_mean/std
+materialization_ms_mean/std
+static_injection_ms_mean/std
+first_result_overhead_ms_mean/std
+peak_rss_mb_mean/std
+mean_cpu_percent_mean/std
+```
+
+## Experiment B: baseline-cardinality scaling
+
+This experiment fixes the historical log size and varies the number of baseline entities.
+
+It answers:
+
+```text
+How do materialization and static graph injection scale as the baseline relation grows?
+```
+
+Run:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 1 \
+  --runs 3 \
+  --historical-events 1M \
+  --baseline-entities 1,10,100,1000,10000
+```
+
+Expected interpretation:
+
+```text
+Historical baseline evaluation should stay in roughly the same range because the historical log size is fixed.
+Materialization and static graph injection should increase with baseline cardinality.
+```
+
+Important metrics:
+
+```text
+baseline_entities
+baseline_binding_count_mean
+materialized_quad_count_mean
+baseline_eval_ms_mean/std
+materialization_ms_mean/std
+static_injection_ms_mean/std
+peak_rss_mb_mean/std
+mean_cpu_percent_mean/std
+```
+
+## Experiment C: realtime live replay sanity check
+
+This experiment validates live behavior under wall-clock pacing.
+
+It answers:
+
+```text
+Does the baseline variant preserve live-window behavior when events arrive in realtime?
+```
+
+Run:
+
+```bash
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 10000 \
+  --baseline-entities 10 \
+  --live-replay-mode realtime \
+  --live-rate-hz 4 \
+  --live-duration-seconds 240 \
+  --live-window-size-seconds 120 \
+  --live-window-slide-seconds 60
+```
+
+Expected behavior:
+
+```text
+live_event_count = 960
+expected_emitted_windows = 4
+expected_full_windows = 3
+warmup_window_count = 1
+observed_baseline_rows = 40
+observed_live_only_rows = 40
+correctness_passed = true
+```
+
+The first result should appear around the first slide boundary, approximately 60 seconds.
+
+## CLI options
+
+### Historical event counts
+
+The benchmark accepts raw integers:
+
+```bash
+--historical-events 1000000,5000000,10000000
+```
+
+It also accepts uppercase shorthand:
+
+```bash
+--historical-events 1K,10K,1M,5M,10M
+```
+
+Lowercase `m` is not used for million, to avoid confusion with minutes.
+
+### Baseline entity counts
+
+```bash
+--baseline-entities 1,10,100,1000,10000
+```
+
+### Runs and warmups
+
+```bash
+--warmup-runs 1
+--runs 3
+```
+
+Warmup runs are excluded from the summary statistics.
+
+### Live replay mode
+
+```bash
+--live-replay-mode accelerated
+--live-replay-mode realtime
+```
+
+Default:
+
+```text
+accelerated
+```
+
+### Realtime live options
+
+```bash
+--live-rate-hz 4
+--live-duration-seconds 240
+--live-window-size-seconds 120
+--live-window-slide-seconds 60
+```
+
+### Verbose output
+
+```bash
+--verbose
+```
+
+Verbose mode prints per-run details and internal progress logs.
+
+### Debug lowered query
+
+```bash
+--debug-lowered-query
+```
+
+This prints the lowered live query with line numbers. It is useful for debugging parser/lowering failures.
+
+## Output artifacts
+
+Each benchmark run writes to:
+
+```text
+logs/benchmark/query_defined_baseline/<timestamp>/
+```
+
+The main files are:
+
+```text
+query_defined_baseline.raw.json
+query_defined_baseline.summary.csv
+query_defined_baseline_results.md
+```
+
+### Raw JSON
+
+Contains per-run measurements and correctness diagnostics.
+
+Useful for debugging and detailed inspection.
+
+### Summary CSV
+
+Contains one row per configuration with mean/std metrics.
+
+Useful for plotting and paper table generation.
+
+### Markdown summary
+
+Contains a compact paper-readable table.
+
+Useful for quickly copying results into notes or drafts.
+
+## Resource metrics
+
+The benchmark samples whole-process CPU and memory usage.
+
+Recorded metrics include:
+
+```text
+peak_rss_mb
+mean_rss_mb
+peak_cpu_percent
+mean_cpu_percent
+sample_count
+```
+
+These are whole-run process measurements. They include historical generation, storage writes, baseline evaluation, materialization, static injection, and live replay. They are not phase-isolated.
+
+CPU percentages above 100% can occur if multiple cores/threads are active.
+
+## Recommended server workflow
+
+Run benchmarks inside `tmux` so the process survives SSH disconnects:
+
+```bash
+tmux new -s janus-bench
+```
+
+Inside the session:
+
+```bash
+cargo build --release
+cargo test -- --nocapture
+
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 10K \
+  --baseline-entities 10
+
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 1 \
+  --runs 3 \
+  --historical-events 1M,5M,10M \
+  --baseline-entities 10
+
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 1 \
+  --runs 3 \
+  --historical-events 1M \
+  --baseline-entities 1,10,100,1000,10000
+
+cargo run --release --bin paper_query_defined_baseline -- \
+  --warmup-runs 0 \
+  --runs 1 \
+  --historical-events 10000 \
+  --baseline-entities 10 \
+  --live-replay-mode realtime \
+  --live-rate-hz 4 \
+  --live-duration-seconds 240 \
+  --live-window-size-seconds 120 \
+  --live-window-slide-seconds 60
+```
+
+Detach from `tmux` with:
+
+```text
+Ctrl+b, then d
+```
+
+Reattach with:
+
+```bash
+tmux attach -t janus-bench
+```
+
+## Archiving results
+
+After running experiments, archive the benchmark outputs:
+
+```bash
+tar -czf janus_query_defined_baseline_results_$(date +%Y%m%d_%H%M%S).tar.gz \
+  logs/benchmark/query_defined_baseline
+```
+
+Also save the server metadata:
+
+```bash
+{
+  echo "date=$(date -Iseconds)"
+  echo "host=$(hostname)"
+  echo "commit=$(git rev-parse HEAD)"
+  echo "rustc=$(rustc --version)"
+  echo "cargo=$(cargo --version)"
+  echo
+  uname -a
+  echo
+  lscpu
+  echo
+  free -h
+  echo
+  df -h .
+} > logs/benchmark/server_metadata_$(date +%Y%m%d_%H%M%S).txt
+```
+
+## Paper interpretation
+
+The benchmark is intended to support the following claims:
+
+```text
+1. Query-defined baselines are evaluated over the historical log before live processing starts.
+
+2. The resulting baseline bindings are materialized into a static named graph using the explicit GRAPH template in the registered query.
+
+3. The live query can then use this static baseline graph together with live stream windows.
+
+4. Historical baseline evaluation cost grows with historical log size.
+
+5. GRAPH-template materialization and static graph injection scale with the number of baseline rows/quads.
+
+6. For small baseline relations, materialization and injection are negligible compared with historical evaluation.
+
+7. Realtime replay confirms that the query-defined baseline variant preserves live-window emission behavior under wall-clock event arrival.
+```
+
+Important caveat:
+
+```text
+The benchmark currently reports whole-process RSS and CPU usage. Memory usage can grow substantially with historical event count and baseline cardinality, so memory results should be reported explicitly rather than hidden.
+```
diff --git a/docs/QUICKSTART_HTTP_API.md b/docs/QUICKSTART_HTTP_API.md
index ade4df4..5f3682a 100644
--- a/docs/QUICKSTART_HTTP_API.md
+++ b/docs/QUICKSTART_HTTP_API.md
@@ -22,7 +22,7 @@ curl -X POST http://localhost:8080/api/queries \
   -H "Content-Type: application/json" \
   -d '{
     "query_id": "test_query",
-    "janusql": "PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:w ON STREAM ex:sensorStream [START 0 END 9999999999999] WHERE { WINDOW ex:w { ?s ?p ?o . } }"
+    "janusql": "PREFIX ex: <http://example.org/> SELECT ?s ?p ?o FROM NAMED WINDOW ex:w ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:w { ?s ?p ?o . } }"
   }'
 ```
 
diff --git a/docs/README.md b/docs/README.md
index 0d95628..57bf9d6 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -17,6 +17,7 @@ This directory contains the current Janus documentation.
 ## Supporting Material
 
 - [BENCHMARK_RESULTS.md](./BENCHMARK_RESULTS.md): benchmark data
+- [BENCHMARKING.md](./BENCHMARKING.md): current benchmark harness and run commands
 - [STREAM_BUS_CLI.md](./STREAM_BUS_CLI.md): replay and ingestion CLI
 
 ## Repo Boundary
diff --git a/docs/README_HTTP_API.md b/docs/README_HTTP_API.md
index f048770..0848c0b 100644
--- a/docs/README_HTTP_API.md
+++ b/docs/README_HTTP_API.md
@@ -29,7 +29,7 @@ curl -X POST http://localhost:8080/api/queries \
   -H "Content-Type: application/json" \
   -d '{
     "query_id": "sensor_analysis",
-    "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:w ON STREAM ex:sensorStream [START 0 END 9999999999999] WHERE { WINDOW ex:w { ?sensor ex:temperature ?temp . } }"
+    "janusql": "PREFIX ex: <http://example.org/> SELECT ?sensor ?temp FROM NAMED WINDOW ex:w ON STREAM ex:graph1 [START 0 END 9999999999999] WHERE { WINDOW ex:w { ?sensor ex:temperature ?temp . } }"
   }'
 ```
 
diff --git a/docs/decisions/2026-06-10-hybrid-scaling-metrics.md b/docs/decisions/2026-06-10-hybrid-scaling-metrics.md
new file mode 100644
index 0000000..aaa8468
--- /dev/null
+++ b/docs/decisions/2026-06-10-hybrid-scaling-metrics.md
@@ -0,0 +1,25 @@
+# H1.1 Benchmarking Metrics and Representation
+
+Date: 2026-06-10
+
+## Status
+
+Accepted
+
+## Context
+
+The H1.1 benchmark validates Janus unified versus decomposed Oxigraph equivalence. To clarify the role of the live-streaming query component and coordinate join stages, the benchmark must clearly delineate the latencies of individual query steps (historical query, live-stream processing, and external join/combination).
+
+## Decision
+
+1. Rename the decomposed baseline to `"Oxigraph historical + Janus live window processor + external join"`.
+2. Measure and report latencies:
+   - `live_stream_processing_latency_ms`: Calculated as `first_result_engine - first_event_published` since live stream events are added back-to-back.
+   - `external_join_latency_ms`: Set to `0.0` for JanusUnified. For Decomposed, calculated as the client-side join execution duration.
+   - `first_hybrid_result_latency_ms`: Set to the total time from query registration/launch to client-side final output.
+3. Compare final hybrid result correctness (`result_hash` and `result_count`) for the primary equivalence assertion, while reporting historical and live equivalence separately.
+
+## Alternatives Considered
+
+- **Zero-latency assumption for Janus hybrid combination**: Rejected because hybrid combination still occurs inline within the engine for Janus unified. An external client-side join duration is instead represented by `external_join_latency_ms`.
+- **Excluding live intermediate result hash**: Accepted because `Janus Unified` executes the join inline and does not generate a separate live intermediate result. Live intermediate result equivalence is labeled as not applicable, but final hybrid and historical queries are verified.
diff --git a/docs/decisions/2026-06-10-sustained-hybrid-execution.md b/docs/decisions/2026-06-10-sustained-hybrid-execution.md
new file mode 100644
index 0000000..178c459
--- /dev/null
+++ b/docs/decisions/2026-06-10-sustained-hybrid-execution.md
@@ -0,0 +1,26 @@
+# H1.2 Sustained Hybrid Window Execution Design
+
+Date: 2026-06-10
+
+## Status
+
+Accepted
+
+## Context
+
+The H1.2 benchmark evaluates sustained query execution over continuous sliding windows. Unlike H1.1 which focuses on first-result latency, H1.2 must measure latency and data transfer over repeated windows during virtual event-time streaming.
+
+## Decision
+
+1. Treat live-duration-seconds as logical event-time duration. Output logical_live_duration_seconds.
+2. Record wall_clock_benchmark_duration_ms and uses_virtual_event_time: true.
+3. Represent windows using canonical bounds: window_start_ms, window_end_ms, and window_id: window_start_ms + "-" + window_end_ms. Use these bounds for per-window hashing and equivalence checks.
+4. Introduce a 2ms sleep during event addition to resolve the race condition with asynchronous window evaluation inside the streaming processor, ensuring deterministic window collection.
+5. Introduce a sentinel watermark event at the end of duration (last timestamp + 20 seconds) to deterministically trigger finalization of active windows.
+6. Exclude out-of-horizon and sentinel-finalized flush windows from summary statistics (latency, result count, and data transfer size) by default. Add completed_windows_total, completed_windows_in_horizon, and flush_windows metrics, and perform validation checks strictly on the horizon windows.
+
+## Alternatives Considered
+
+- Wall-clock time execution: Rejected because running the benchmark in real-time is slow, non-deterministic, and prone to CPU scheduling jitter. Virtual event-time streaming is fast and reproducible.
+- Single timestamp window keys: Rejected because window start times alone do not represent window bounds. Combining start and end timestamps into a canonical string key window_id allows precise equivalence validation across sliding windows.
+- Polling with long sleeps: Rejected because long sleeps slow down the benchmark. A minimal 2ms sleep after each event addition provides enough context-yield time for the background streaming processor thread to emit results without significantly impacting wall-clock duration.
diff --git a/examples/http_client_example.rs b/examples/http_client_example.rs
index cb45453..893d5ec 100644
--- a/examples/http_client_example.rs
+++ b/examples/http_client_example.rs
@@ -109,6 +109,10 @@ struct QueryResultMessage {
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
     let base_url = "http://127.0.0.1:8080";
     let client = reqwest::Client::new();
+    let mut had_errors = false;
+    let run_id = std::time::SystemTime::now().duration_since(std::time::UNIX_EPOCH)?.as_secs();
+    let sensor_query_id = format!("sensor_query_{run_id}");
+    let live_query_id = format!("live_sensor_query_{run_id}");
 
     println!("╔════════════════════════════════════════════════════════════════╗");
     println!("║         Janus HTTP API Client Example                         ║");
@@ -155,11 +159,11 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     println!("2. Register a Query");
     println!("   POST {}/api/queries", base_url);
     let query_request = RegisterQueryRequest {
-        query_id: "sensor_query_1".to_string(),
+        query_id: sensor_query_id.clone(),
         janusql: r#"
             PREFIX ex: <http://example.org/>
             SELECT ?sensor ?temp ?time
-            FROM NAMED WINDOW ex:histWindow ON STREAM ex:sensorStream [START 1704067200 END 1704153600]
+            FROM NAMED WINDOW ex:histWindow ON STREAM ex:graph1 [START 0 END 9999999999999]
             WHERE {
                 WINDOW ex:histWindow {
                     ?sensor ex:temperature ?temp .
@@ -184,6 +188,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     } else {
         let error_text = response.text().await?;
         println!("   ✗ Registration failed: {}", error_text);
+        had_errors = true;
     }
     println!();
 
@@ -191,11 +196,11 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     println!("3. Register Another Query (Live Stream)");
     println!("   POST {}/api/queries", base_url);
     let live_query_request = RegisterQueryRequest {
-        query_id: "live_sensor_query".to_string(),
+        query_id: live_query_id.clone(),
         janusql: r#"
             PREFIX ex: <http://example.org/>
             SELECT ?sensor ?temp
-            FROM NAMED WINDOW ex:liveWindow ON STREAM ex:sensorStream [RANGE 10000 STEP 5000]
+            FROM NAMED WINDOW ex:liveWindow ON STREAM ex:graph1 [RANGE 10000 STEP 5000]
             WHERE {
                 WINDOW ex:liveWindow {
                     ?sensor ex:temperature ?temp .
@@ -219,6 +224,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     } else {
         let error_text = response.text().await?;
         println!("   ✗ Registration failed: {}", error_text);
+        had_errors = true;
     }
     println!();
 
@@ -235,13 +241,17 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         }
     } else {
         println!("   ✗ Failed to list queries");
+        had_errors = true;
     }
     println!();
 
     // 5. Get Query Details
     println!("5. Get Query Details");
-    println!("   GET {}/api/queries/sensor_query_1", base_url);
-    let response = client.get(format!("{}/api/queries/sensor_query_1", base_url)).send().await?;
+    println!("   GET {}/api/queries/{}", base_url, sensor_query_id);
+    let response = client
+        .get(format!("{}/api/queries/{}", base_url, sensor_query_id))
+        .send()
+        .await?;
 
     if response.status().is_success() {
         let body: QueryDetailsResponse = response.json().await?;
@@ -253,6 +263,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         println!("   ✓ Status: {}", body.status);
     } else {
         println!("   ✗ Failed to get query details");
+        had_errors = true;
     }
     println!();
 
@@ -280,6 +291,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     } else {
         let error_text = response.text().await?;
         println!("   ✗ Replay start failed: {}", error_text);
+        had_errors = true;
     }
     println!();
 
@@ -300,14 +312,15 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         println!("   ✓ Elapsed: {:.2}s", body.elapsed_seconds);
     } else {
         println!("   ✗ Failed to get replay status");
+        had_errors = true;
     }
     println!();
 
     // 8. Start Query Execution
     println!("8. Start Query Execution");
-    println!("   POST {}/api/queries/sensor_query_1/start", base_url);
+    println!("   POST {}/api/queries/{}/start", base_url, sensor_query_id);
     let response = client
-        .post(format!("{}/api/queries/sensor_query_1/start", base_url))
+        .post(format!("{}/api/queries/{}/start", base_url, sensor_query_id))
         .send()
         .await?;
 
@@ -317,17 +330,18 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     } else {
         let error_text = response.text().await?;
         println!("   ✗ Query start failed: {}", error_text);
+        had_errors = true;
     }
     println!();
 
     // 9. WebSocket Connection for Streaming Results
     println!("9. Connect to WebSocket for Query Results");
-    println!("   WS ws://127.0.0.1:8080/api/queries/sensor_query_1/results");
+    println!("   WS ws://127.0.0.1:8080/api/queries/{}/results", sensor_query_id);
     println!("   (Streaming results for 5 seconds...)");
 
-    let ws_url = "ws://127.0.0.1:8080/api/queries/sensor_query_1/results";
+    let ws_url = format!("ws://127.0.0.1:8080/api/queries/{}/results", sensor_query_id);
 
-    match tokio_tungstenite::connect_async(ws_url).await {
+    match tokio_tungstenite::connect_async(&ws_url).await {
         Ok((mut ws_stream, _)) => {
             use futures_util::StreamExt;
             use tokio_tungstenite::tungstenite::Message;
@@ -357,6 +371,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
                                     }
                                     Err(e) => {
                                         println!("   ✗ Failed to parse result: {}", e);
+                                        had_errors = true;
                                     }
                                 }
                             }
@@ -366,6 +381,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
                             }
                             Some(Err(e)) => {
                                 println!("   ✗ WebSocket error: {}", e);
+                                had_errors = true;
                                 break;
                             }
                             None => {
@@ -383,18 +399,26 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
             }
 
             println!("   ✓ Received {} results", result_count);
+            if result_count == 0 {
+                println!("   ✗ Query returned no result messages");
+                had_errors = true;
+            }
         }
         Err(e) => {
             println!("   ✗ WebSocket connection failed: {}", e);
-            println!("   (This is expected if the query has no results yet)");
+            println!("   (The query should already have results at this point)");
+            had_errors = true;
         }
     }
     println!();
 
     // 10. Stop Query
     println!("10. Stop Query Execution");
-    println!("   DELETE {}/api/queries/sensor_query_1", base_url);
-    let response = client.delete(format!("{}/api/queries/sensor_query_1", base_url)).send().await?;
+    println!("   POST {}/api/queries/{}/stop", base_url, sensor_query_id);
+    let response = client
+        .post(format!("{}/api/queries/{}/stop", base_url, sensor_query_id))
+        .send()
+        .await?;
 
     if response.status().is_success() {
         let body: SuccessResponse = response.json().await?;
@@ -402,23 +426,62 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     } else {
         let error_text = response.text().await?;
         println!("   ✗ Query stop failed: {}", error_text);
+        had_errors = true;
+    }
+    println!();
+
+    // 11. Delete Registered Queries
+    println!("11. Delete Registered Queries");
+    for query_id in [&sensor_query_id, &live_query_id] {
+        println!("   DELETE {}/api/queries/{}", base_url, query_id);
+        let response =
+            client.delete(format!("{}/api/queries/{}", base_url, query_id)).send().await?;
+
+        if response.status().is_success() {
+            let body: SuccessResponse = response.json().await?;
+            println!("   ✓ {}", body.message);
+        } else {
+            let error_text = response.text().await?;
+            println!("   ✗ Query delete failed for {}: {}", query_id, error_text);
+            had_errors = true;
+        }
     }
     println!();
 
-    // 11. Stop Replay
-    println!("11. Stop Stream Bus Replay");
-    println!("   POST {}/api/replay/stop", base_url);
-    let response = client.post(format!("{}/api/replay/stop", base_url)).send().await?;
+    // 12. Replay Cleanup
+    println!("12. Replay Cleanup");
+    println!("   GET {}/api/replay/status", base_url);
+    let response = client.get(format!("{}/api/replay/status", base_url)).send().await?;
 
     if response.status().is_success() {
-        let body: SuccessResponse = response.json().await?;
-        println!("   ✓ {}", body.message);
+        let body: ReplayStatusResponse = response.json().await?;
+        if body.is_running {
+            println!("   POST {}/api/replay/stop", base_url);
+            let stop_response = client.post(format!("{}/api/replay/stop", base_url)).send().await?;
+            if stop_response.status().is_success() {
+                let body: SuccessResponse = stop_response.json().await?;
+                println!("   ✓ {}", body.message);
+            } else {
+                let error_text = stop_response.text().await?;
+                println!("   ✗ Replay stop failed: {}", error_text);
+                had_errors = true;
+            }
+        } else {
+            println!("   ✓ Replay already completed");
+        }
     } else {
-        let error_text = response.text().await?;
-        println!("   ✗ Replay stop failed: {}", error_text);
+        println!("   ✗ Failed to get replay status");
+        had_errors = true;
     }
     println!();
 
+    if had_errors {
+        println!("╔════════════════════════════════════════════════════════════════╗");
+        println!("║             Example Completed With Errors                      ║");
+        println!("╚════════════════════════════════════════════════════════════════╝");
+        return Err("one or more HTTP example steps failed".into());
+    }
+
     println!("╔════════════════════════════════════════════════════════════════╗");
     println!("║              Example Completed Successfully                    ║");
     println!("╚════════════════════════════════════════════════════════════════╝");
diff --git a/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_fixed_60s_janus_vs_oxigraph.png b/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_fixed_60s_janus_vs_oxigraph.png
new file mode 100644
index 0000000..38f55a5
Binary files /dev/null and b/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_fixed_60s_janus_vs_oxigraph.png differ
diff --git a/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_range_comparison_results.md b/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_range_comparison_results.md
new file mode 100644
index 0000000..87dacfc
--- /dev/null
+++ b/logs/benchmark/paper_historical_range_comparison/1781267057740/h2_range_comparison_results.md
@@ -0,0 +1,38 @@
+# H2 Historical Timestamp Range Comparison
+
+## Query
+
+Both systems answer the same timestamp range query:
+
+timestamp >= X
+timestamp < Y
+
+Janus executes this as a historical range lookup over its event-log structure.
+
+Oxigraph executes this as SPARQL over the same RDF quads:
+
+SELECT ?event ?t
+WHERE {
+  ?event <http://example.org/schema/timestamp> ?t .
+  FILTER (?t >= X && ?t < Y)
+}
+
+## Result
+
+| Query Case | 10k quads | 50k quads | 100k quads | 500k quads | Takeaway |
+| --- | ---: | ---: | ---: | ---: | --- |
+| Janus fixed 60s |  |  |  |  | Bounded timestamp lookup |
+| Oxigraph fixed 60s FILTER |  |  |  |  | SPARQL timestamp filter |
+| Janus full history |  |  |  |  | Full historical read |
+| Oxigraph full history FILTER |  |  |  |  | Full timestamp-filter scan |
+
+| Query Case | 10k | 50k | 100k | 500k |
+| --- | --- | --- | --- | --- |
+| fixed_60s_range | no | no | no | no |
+| full_history_range | no | no | no | no |
+
+## Interpretation
+
+- fixed_60s_range tests bounded lookup over a 60-second historical interval
+- full_history_range tests reading all historical data
+- this directly compares Janus historical retrieval with Oxigraph SPARQL timestamp FILTER over the same RDF event log data
diff --git a/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.raw.jsonl b/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.raw.jsonl
new file mode 100644
index 0000000..f963c06
--- /dev/null
+++ b/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.raw.jsonl
@@ -0,0 +1,2 @@
+{"system":"janus","dataset_size_quads":10,"event_count":10,"query_case":"fixed_60s_range","range_start_ms":1720000000000,"range_end_ms":1720000060000,"range_width_ms":60000,"result_count":10,"result_hash":"307b826fe3a4eab9ad8e5bb21bbefb6ecf50bd13dded171b7836b1d49695e5d5","equivalent_to_baseline":true,"latency_ms":0.194291,"run_id":0,"is_warmup":false,"mode":"cold"}
+{"system":"oxigraph","dataset_size_quads":10,"event_count":10,"query_case":"fixed_60s_range","range_start_ms":1720000000000,"range_end_ms":1720000060000,"range_width_ms":60000,"result_count":10,"result_hash":"307b826fe3a4eab9ad8e5bb21bbefb6ecf50bd13dded171b7836b1d49695e5d5","equivalent_to_baseline":true,"latency_ms":1.077375,"run_id":0,"is_warmup":false,"mode":"cold"}
diff --git a/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.summary.csv b/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.summary.csv
new file mode 100644
index 0000000..b7d4a44
--- /dev/null
+++ b/logs/benchmark/paper_historical_range_comparison/1781267057740/paper_historical_range_comparison.summary.csv
@@ -0,0 +1,2 @@
+dataset_size_quads,query_case,range_width_ms,result_count,janus_p50_ms,oxigraph_p50_ms,janus_p95_ms,oxigraph_p95_ms,janus_avg_ms,oxigraph_avg_ms,ratio_oxigraph_over_janus,equivalent
+10,fixed_60s_range,60000,10,0.194,1.077,0.194,1.077,0.194,1.077,5.545,true
diff --git a/logs/benchmark/paper_historical_scaling/1781266987667/logs/citybench_10.nq b/logs/benchmark/paper_historical_scaling/1781266987667/logs/citybench_10.nq
new file mode 100644
index 0000000..853f127
--- /dev/null
+++ b/logs/benchmark/paper_historical_scaling/1781266987667/logs/citybench_10.nq
@@ -0,0 +1,10 @@
+1720000000000 <http://example.org/junction/0> <http://example.org/trafficFlow> "20" <http://example.org/citybench> .
+1720000000001 <http://example.org/junction/1> <http://example.org/trafficFlow> "21" <http://example.org/citybench> .
+1720000000002 <http://example.org/junction/2> <http://example.org/trafficFlow> "22" <http://example.org/citybench> .
+1720000000003 <http://example.org/junction/3> <http://example.org/trafficFlow> "23" <http://example.org/citybench> .
+1720000000004 <http://example.org/junction/4> <http://example.org/trafficFlow> "24" <http://example.org/citybench> .
+1720000000005 <http://example.org/junction/5> <http://example.org/trafficFlow> "25" <http://example.org/citybench> .
+1720000000006 <http://example.org/junction/6> <http://example.org/trafficFlow> "26" <http://example.org/citybench> .
+1720000000007 <http://example.org/junction/7> <http://example.org/trafficFlow> "27" <http://example.org/citybench> .
+1720000000008 <http://example.org/junction/8> <http://example.org/trafficFlow> "28" <http://example.org/citybench> .
+1720000000009 <http://example.org/junction/9> <http://example.org/trafficFlow> "29" <http://example.org/citybench> .
diff --git a/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.fit.csv b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.fit.csv
new file mode 100644
index 0000000..ed43d35
--- /dev/null
+++ b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.fit.csv
@@ -0,0 +1,2 @@
+query_type,mode,slope_ms_per_100k_quads,intercept_ms,r_squared,number_of_points
+point_lookup,cold,0.000000,0.517750,1.000000,1
diff --git a/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.raw.jsonl b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.raw.jsonl
new file mode 100644
index 0000000..186c871
--- /dev/null
+++ b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.raw.jsonl
@@ -0,0 +1 @@
+{"dataset_size_quads":10,"query_type":"point_lookup","mode":"cold","is_warmup":false,"run_index":0,"logical_quads_scanned":0,"selectivity":0.0,"result_count":0,"result_hash":"4f53cda18c2baa0c0354bb5f9a3ecbe5ed12ab4d8e11ba873c2f11161202b945","latency_ms":0.5177499999999999,"p50_latency_ms":0.5177499999999999,"p95_latency_ms":0.5177499999999999,"throughput_quads_per_sec":0.0,"peak_rss_mb":10.15625,"metadata":{"git_commit_sha":"b9da83e012fb88997265b533077f218fa5453236","branch":"benchmark-paper-hybrid-scaling","rustc_version":"rustc 1.90.0 (1159e78c4 2025-09-14)","os":"macos 25.5.0","cpu_model":"Apple M4","ram_bytes":17179869184,"benchmark_command":"target/release/paper_historical_scaling --warmup-runs 0 --runs 1 --dataset-sizes 10 --query-types point-lookup --mode cold","timestamp_unix_ms":1781266987742}}
diff --git a/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.summary.csv b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.summary.csv
new file mode 100644
index 0000000..ca32ff5
--- /dev/null
+++ b/logs/benchmark/paper_historical_scaling/1781266987667/paper_historical_scaling.summary.csv
@@ -0,0 +1,2 @@
+dataset_size_quads,query_type,mode,runs,logical_quads_scanned,selectivity,result_count,p50_latency_ms,p95_latency_ms,avg_latency_ms,avg_throughput_quads_per_sec,max_peak_rss_mb
+10,point_lookup,cold,1,0,0.000000,0,0.518,0.518,0.518,0.000,10.156
diff --git a/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.raw.jsonl b/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.raw.jsonl
new file mode 100644
index 0000000..38a09d1
--- /dev/null
+++ b/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.raw.jsonl
@@ -0,0 +1,2 @@
+{"system":"janus_unified","mode":"cold","is_warmup":false,"run_index":0,"historical_events":10,"live_events":3,"client_start":1781267011240,"query_registered":1781267011240,"historical_start":1781267011240,"historical_done":1781267011241,"live_ready":1781267011241,"first_event_published":1781267011241,"first_result_engine":1781267011241,"first_result_client":1781267011251,"e2e_latency_ms":11.0,"estimated_useful_engine_work_ms":1.0,"estimated_coordination_overhead_ms":10.0,"historical_intermediate_bytes":1131,"live_intermediate_bytes":352,"estimated_external_transfer_bytes":0,"final_result_bytes":238,"components":1,"process_boundaries":0,"serialization_steps":1,"result_count":3,"historical_input_hash":"7911be48b32577814be088aa2de9fa7feb868ae85616bb18b9101b0b42add671","live_input_hash":"028a07a12e41e0e79743c42eee8b6ad8b7b5e29104a7c318c2fe74587e0ce365","result_hash":"4e1712cf8801b5a3ead6646fc077932ca809f08e907fbe62dd5604d8eaace375","equivalent_to_baseline":true,"metadata":{"git_commit_sha":"b9da83e012fb88997265b533077f218fa5453236","branch":"benchmark-paper-hybrid-scaling","rustc_version":"rustc 1.90.0 (1159e78c4 2025-09-14)","os":"macos 25.5.0","cpu_model":"Apple M4","ram_bytes":17179869184,"benchmark_command":"target/release/paper_hybrid_coordination --warmup-runs 0 --runs 1 --historical-events 10 --live-events 3 --mode cold","timestamp_unix_ms":1781267011239},"live_events_published":3,"live_events_processed":3,"live_window_size":10000,"live_window_slide":1000,"live_query_registered_at":1781267011240,"live_first_event_at":1900000000000,"live_first_window_result_at":1781267011241,"live_stream_processing_latency_ms":0.0,"external_join_latency_ms":0.0,"first_hybrid_result_latency_ms":11.0,"historical_result_count":10,"historical_result_hash":"f66d48a151b98ad1d61429493d7c5e2c848a5ec77eeeca000b1cd70b3d2b7877","live_result_count":0,"live_result_hash":null,"hybrid_result_count":3,"hybrid_result_hash":"4e1712cf8801b5a3ead6646fc077932ca809f08e907fbe62dd5604d8eaace375","historical_equivalent_to_baseline":true,"hybrid_equivalent_to_baseline":true}
+{"system":"Oxigraph historical + Janus live window processor + external join","mode":"cold","is_warmup":false,"run_index":0,"historical_events":10,"live_events":3,"client_start":1781267011252,"query_registered":1781267011252,"historical_start":1781267011252,"historical_done":1781267011252,"live_ready":1781267011252,"first_event_published":1781267011252,"first_result_engine":1781267011252,"first_result_client":1781267011262,"e2e_latency_ms":10.0,"estimated_useful_engine_work_ms":0.0,"estimated_coordination_overhead_ms":10.0,"historical_intermediate_bytes":691,"live_intermediate_bytes":352,"estimated_external_transfer_bytes":1043,"final_result_bytes":238,"components":4,"process_boundaries":3,"serialization_steps":4,"result_count":3,"historical_input_hash":"7911be48b32577814be088aa2de9fa7feb868ae85616bb18b9101b0b42add671","live_input_hash":"028a07a12e41e0e79743c42eee8b6ad8b7b5e29104a7c318c2fe74587e0ce365","result_hash":"4e1712cf8801b5a3ead6646fc077932ca809f08e907fbe62dd5604d8eaace375","equivalent_to_baseline":null,"metadata":{"git_commit_sha":"b9da83e012fb88997265b533077f218fa5453236","branch":"benchmark-paper-hybrid-scaling","rustc_version":"rustc 1.90.0 (1159e78c4 2025-09-14)","os":"macos 25.5.0","cpu_model":"Apple M4","ram_bytes":17179869184,"benchmark_command":"target/release/paper_hybrid_coordination --warmup-runs 0 --runs 1 --historical-events 10 --live-events 3 --mode cold","timestamp_unix_ms":1781267011239},"live_events_published":3,"live_events_processed":3,"live_window_size":10000,"live_window_slide":1000,"live_query_registered_at":1781267011252,"live_first_event_at":1900000000000,"live_first_window_result_at":1781267011252,"live_stream_processing_latency_ms":0.0,"external_join_latency_ms":10.0,"first_hybrid_result_latency_ms":10.0,"historical_result_count":10,"historical_result_hash":"f66d48a151b98ad1d61429493d7c5e2c848a5ec77eeeca000b1cd70b3d2b7877","live_result_count":3,"live_result_hash":"6cec8ade37db60b8f1d699cf9c5ac64bb4a08673a580ae47874d6df97005a93b","hybrid_result_count":3,"hybrid_result_hash":"4e1712cf8801b5a3ead6646fc077932ca809f08e907fbe62dd5604d8eaace375","historical_equivalent_to_baseline":null,"hybrid_equivalent_to_baseline":null}
diff --git a/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.summary.csv b/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.summary.csv
new file mode 100644
index 0000000..551d661
--- /dev/null
+++ b/logs/benchmark/paper_hybrid_coordination/1781267011162/paper_hybrid_coordination.summary.csv
@@ -0,0 +1,3 @@
+system,mode,runs,components,process_boundaries,serialization_steps,p50_e2e_latency_ms,p95_e2e_latency_ms,avg_useful_engine_work_ms,avg_coordination_overhead_ms,avg_external_transfer_bytes,avg_final_result_bytes,avg_result_count,avg_live_events_published,avg_live_events_processed,avg_live_stream_processing_latency_ms,avg_external_join_latency_ms,avg_first_hybrid_result_latency_ms,avg_historical_result_count,avg_live_result_count,avg_hybrid_result_count,historical_equivalence_rate,hybrid_equivalence_rate
+Oxigraph historical + Janus live window processor + external join,cold,1,4,3,4,10.000,10.000,0.000,10.000,1043.000,238.000,3.000,3.000,3.000,0.000,10.000,10.000,10.000,3.000,3.000,0.000,0.000
+janus_unified,cold,1,1,0,1,11.000,11.000,1.000,10.000,0.000,238.000,3.000,3.000,3.000,0.000,0.000,11.000,10.000,0.000,3.000,1.000,1.000
diff --git a/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.raw.jsonl b/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.raw.jsonl
new file mode 100644
index 0000000..7a1e9c7
--- /dev/null
+++ b/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.raw.jsonl
@@ -0,0 +1,2 @@
+{"system":"janus_unified","mode":"cold","time_mode":"virtual","is_warmup":false,"run_index":0,"historical_events":10,"logical_live_duration_seconds":1,"event_rate_hz":1,"event_interval_ms":1000.0,"expected_wall_clock_duration_ms":1000,"events_published":1,"events_processed":1,"window_size_ms":1000,"window_slide_ms":1000,"expected_completed_windows":1,"completed_windows_total":1,"completed_windows_in_horizon":1,"flush_windows":0,"missed_windows":0,"historical_start_at":1781267034760,"historical_ready_at":1781267034760,"live_start_at":1781267034761,"first_live_event_at":1900000000000,"first_live_window_ready_at":1781267034776,"first_hybrid_result_at":1781267034776,"historical_preparation_latency_ms":0.0,"first_live_window_latency_ms":15.0,"first_hybrid_result_latency_ms":16.0,"first_hybrid_result_wall_clock_ms":15.080375,"readiness_gap_ms":16.0,"hybrid_wait_after_inputs_ready_ms":0.0,"p50_window_hybrid_latency_ms":0.012833,"p95_window_hybrid_latency_ms":0.012833,"window_result_wall_clock_offsets_ms":[15.080375],"p50_window_result_wall_clock_offset_ms":15.080375,"p95_window_result_wall_clock_offset_ms":15.080375,"external_join_latency_total_ms":-0.0,"external_join_latency_avg_ms":-0.0,"estimated_external_transfer_bytes_total":0,"estimated_external_transfer_bytes_per_window":0,"hybrid_result_count_total":1,"hybrid_result_hash_total":"36f13bb32e7eb514609efca61ed938568e516ed90dc750ad0455ffbd61bfcdb0","equivalent_to_baseline":true,"metadata":{"git_commit_sha":"b9da83e012fb88997265b533077f218fa5453236","branch":"benchmark-paper-hybrid-scaling","rustc_version":"rustc 1.90.0 (1159e78c4 2025-09-14)","os":"macos 25.5.0","cpu_model":"Apple M4","ram_bytes":17179869184,"benchmark_command":"target/release/paper_sustained_hybrid --warmup-runs 0 --runs 1 --historical-events 10 --live-duration-seconds 1 --event-rate-hz 1 --window-size-seconds 1 --window-slide-seconds 1 --mode cold --time-mode virtual","timestamp_unix_ms":1781267034759},"wall_clock_benchmark_duration_ms":16,"wall_clock_overhead_ms":-984.0,"uses_virtual_event_time":true}
+{"system":"Oxigraph historical + Janus live window processor + external join","mode":"cold","time_mode":"virtual","is_warmup":false,"run_index":0,"historical_events":10,"logical_live_duration_seconds":1,"event_rate_hz":1,"event_interval_ms":1000.0,"expected_wall_clock_duration_ms":1000,"events_published":1,"events_processed":1,"window_size_ms":1000,"window_slide_ms":1000,"expected_completed_windows":1,"completed_windows_total":1,"completed_windows_in_horizon":1,"flush_windows":0,"missed_windows":0,"historical_start_at":1781267034777,"historical_ready_at":1781267034777,"live_start_at":1781267034777,"first_live_event_at":1900000000000,"first_live_window_ready_at":1781267034792,"first_hybrid_result_at":1781267034792,"historical_preparation_latency_ms":0.0,"first_live_window_latency_ms":15.0,"first_hybrid_result_latency_ms":15.0,"first_hybrid_result_wall_clock_ms":15.045042,"readiness_gap_ms":15.0,"hybrid_wait_after_inputs_ready_ms":0.0,"p50_window_hybrid_latency_ms":0.028958,"p95_window_hybrid_latency_ms":0.028958,"window_result_wall_clock_offsets_ms":[15.045042],"p50_window_result_wall_clock_offset_ms":15.045042,"p95_window_result_wall_clock_offset_ms":15.045042,"external_join_latency_total_ms":0.02075,"external_join_latency_avg_ms":0.02075,"estimated_external_transfer_bytes_total":751,"estimated_external_transfer_bytes_per_window":751,"hybrid_result_count_total":1,"hybrid_result_hash_total":"36f13bb32e7eb514609efca61ed938568e516ed90dc750ad0455ffbd61bfcdb0","equivalent_to_baseline":null,"metadata":{"git_commit_sha":"b9da83e012fb88997265b533077f218fa5453236","branch":"benchmark-paper-hybrid-scaling","rustc_version":"rustc 1.90.0 (1159e78c4 2025-09-14)","os":"macos 25.5.0","cpu_model":"Apple M4","ram_bytes":17179869184,"benchmark_command":"target/release/paper_sustained_hybrid --warmup-runs 0 --runs 1 --historical-events 10 --live-duration-seconds 1 --event-rate-hz 1 --window-size-seconds 1 --window-slide-seconds 1 --mode cold --time-mode virtual","timestamp_unix_ms":1781267034759},"wall_clock_benchmark_duration_ms":15,"wall_clock_overhead_ms":-985.0,"uses_virtual_event_time":true}
diff --git a/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.summary.csv b/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.summary.csv
new file mode 100644
index 0000000..e8b331c
--- /dev/null
+++ b/logs/benchmark/paper_sustained_hybrid/1781267034681/paper_sustained_hybrid.summary.csv
@@ -0,0 +1,3 @@
+system,mode,time_mode,runs,historical_events,logical_live_duration_seconds,event_rate_hz,event_interval_ms,expected_wall_clock_duration_ms,window_size_ms,window_slide_ms,avg_events_published,avg_events_processed,avg_completed_windows_total,avg_completed_windows_in_horizon,avg_flush_windows,avg_missed_windows,p50_first_hybrid_result_latency_ms,p95_first_hybrid_result_latency_ms,p50_first_hybrid_result_wall_clock_ms,p95_first_hybrid_result_wall_clock_ms,p50_window_hybrid_latency_ms,p95_window_hybrid_latency_ms,p50_window_result_wall_clock_offset_ms,p95_window_result_wall_clock_offset_ms,avg_historical_preparation_latency_ms,avg_first_live_window_latency_ms,avg_readiness_gap_ms,avg_hybrid_wait_after_inputs_ready_ms,avg_external_join_latency_total_ms,avg_external_join_latency_ms,avg_estimated_external_transfer_bytes_total,avg_estimated_external_transfer_bytes_per_window,avg_hybrid_result_count_total,avg_wall_clock_benchmark_duration_ms,avg_wall_clock_overhead_ms,uses_virtual_event_time,equivalence_rate
+Oxigraph historical + Janus live window processor + external join,cold,virtual,1,10,1,1,1000.000,1000,1000,1000,1.000,1.000,1.000,1.000,0.000,0.000,15.000,15.000,15.045,15.045,0.029,0.029,15.045,15.045,0.000,15.000,15.000,0.000,0.021,0.021,751.000,751.000,1.000,15.000,-985.000,true,0.000
+janus_unified,cold,virtual,1,10,1,1,1000.000,1000,1000,1000,1.000,1.000,1.000,1.000,0.000,0.000,16.000,16.000,15.080,15.080,0.013,0.013,15.080,15.080,0.000,15.000,16.000,0.000,-0.000,-0.000,0.000,0.000,1.000,16.000,-984.000,true,1.000
diff --git a/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.raw.json
new file mode 100644
index 0000000..6a6e3ce
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.raw.json
@@ -0,0 +1,97 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1",
+    "timestamp_unix_ms": 1781260300596
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781260300517",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.565625,
+        "baseline_materialization_ms": 0.032875,
+        "static_graph_injection_ms": 0.011042,
+        "live_startup_ms": 0.002167,
+        "first_result_latency_ms": 255.034333,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.034333
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.034333,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.007958000000000002,
+        "first_result_latency_ms": 250.79395799999998,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          250.79395799999998,
+          250.79908299999997,
+          250.79929099999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.79395799999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.79908299999997,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.79929099999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 4.240375000000029
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..e7728a2
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260300517/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,1,1.000,0.566,0.033,0.011,0.002,255.034,255.034,255.034,255.034,255.034,1.000,1.000,1.000,,
+variant,smoke,live_only,1,1.000,,,,0.008,250.794,250.794,250.797,250.799,250.799,3.000,,,,
+comparison,smoke,comparison,1,,,,,,,,,,,,,0.000,4.240
diff --git a/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.raw.json
new file mode 100644
index 0000000..bafbd87
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.raw.json
@@ -0,0 +1,97 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1",
+    "timestamp_unix_ms": 1781260393214
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781260393135",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.5933750000000001,
+        "baseline_materialization_ms": 0.036041000000000004,
+        "static_graph_injection_ms": 0.001458,
+        "live_startup_ms": 0.0115,
+        "first_result_latency_ms": 255.02358400000003,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.02358400000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.02358400000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.006375,
+        "first_result_latency_ms": 255.047792,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.047792,
+          255.05033300000002,
+          255.05041699999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.047792,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.05033300000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.05041699999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.005125,
+      "first_result_overhead_ms": 0.0
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..ac2514f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260393135/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,1,1.000,0.593,0.036,0.001,0.011,255.024,255.024,255.024,255.024,255.024,1.000,1.000,1.000,,
+variant,smoke,live_only,1,1.000,,,,0.006,255.048,255.048,255.050,255.050,255.050,3.000,,,,
+comparison,smoke,comparison,1,,,,,,,,,,,,,0.005,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.raw.json
new file mode 100644
index 0000000..3292133
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.raw.json
@@ -0,0 +1,492 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 5",
+    "timestamp_unix_ms": 1781260757694
+  },
+  "profile": "smoke",
+  "runs": 5,
+  "warmup_runs": 1,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781260757613",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.603417,
+        "baseline_materialization_ms": 0.036166,
+        "static_graph_injection_ms": 0.001583,
+        "live_startup_ms": 0.0027089999999999996,
+        "first_result_latency_ms": 255.028459,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.028459
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.028459,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.002167,
+        "first_result_latency_ms": 255.02312500000002,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.02312500000002,
+          255.02724999999998,
+          255.027375
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.02312500000002,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.02724999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.027375,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0005419999999999995,
+      "first_result_overhead_ms": 0.005333999999976413
+    },
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.26483300000000004,
+        "baseline_materialization_ms": 0.011209,
+        "static_graph_injection_ms": 0.005541,
+        "live_startup_ms": 0.0035,
+        "first_result_latency_ms": 255.03500000000003,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.03500000000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.03500000000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.003459,
+        "first_result_latency_ms": 255.039917,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.039917,
+          255.04454199999998,
+          255.04483300000004
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.039917,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.04454199999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.04483300000004,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00004100000000000024,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 1,
+        "historical_query_ms": 0.281666,
+        "baseline_materialization_ms": 0.010083,
+        "static_graph_injection_ms": 0.005167,
+        "live_startup_ms": 0.0052499999999999995,
+        "first_result_latency_ms": 254.901333,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          254.901333
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 254.901333,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 1,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0067079999999999996,
+        "first_result_latency_ms": 251.232,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          251.232,
+          251.23466700000003,
+          251.234834
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.232,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.23466700000003,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.234834,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 3.6693329999999946
+    },
+    {
+      "run_index": 2,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_query_ms": 0.334042,
+        "baseline_materialization_ms": 0.011625,
+        "static_graph_injection_ms": 0.005458,
+        "live_startup_ms": 0.0053750000000000004,
+        "first_result_latency_ms": 250.08770800000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.08770800000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.08770800000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.006333,
+        "first_result_latency_ms": 255.07075,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.07075,
+          255.074083,
+          255.07429100000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.07075,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.074083,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.07429100000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 3,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 3,
+        "historical_query_ms": 0.336875,
+        "baseline_materialization_ms": 0.010334,
+        "static_graph_injection_ms": 0.006916,
+        "live_startup_ms": 0.005791,
+        "first_result_latency_ms": 250.13774999999998,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.13774999999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.13774999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 3,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.006334,
+        "first_result_latency_ms": 252.44183399999997,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          252.44183399999997,
+          252.446375,
+          252.44662499999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 252.44183399999997,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 252.446375,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 252.44662499999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 4,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 4,
+        "historical_query_ms": 0.32587499999999997,
+        "baseline_materialization_ms": 0.011084,
+        "static_graph_injection_ms": 0.006083,
+        "live_startup_ms": 0.0054589999999999994,
+        "first_result_latency_ms": 255.06216700000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.06216700000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.06216700000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 4,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.004875,
+        "first_result_latency_ms": 253.73537499999998,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          253.73537499999998,
+          253.737333,
+          253.737416
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.73537499999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.737333,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.737416,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0005839999999999995,
+      "first_result_overhead_ms": 1.3267920000000402
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..1e25256
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781260757613/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,6,1.000,0.334,0.011,0.006,0.005,255.028,255.062,253.375,255.028,255.062,1.000,1.000,1.000,,
+variant,smoke,live_only,6,1.000,,,,0.006,255.023,255.071,253.760,255.023,255.074,3.000,,,,
+comparison,smoke,comparison,6,,,,,,,,,,,,,0.000,0.005
diff --git a/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.raw.json
new file mode 100644
index 0000000..63aa9f4
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.raw.json
@@ -0,0 +1,492 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 5",
+    "timestamp_unix_ms": 1781261434431
+  },
+  "profile": "smoke",
+  "runs": 5,
+  "warmup_runs": 1,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781261434353",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.583959,
+        "baseline_materialization_ms": 0.037167,
+        "static_graph_injection_ms": 0.019,
+        "live_startup_ms": 0.001667,
+        "first_result_latency_ms": 254.58733300000003,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          254.58733300000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 254.58733300000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.006458,
+        "first_result_latency_ms": 255.06666700000002,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.06666700000002,
+          255.07179200000002,
+          255.07200000000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06666700000002,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.07179200000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.07200000000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.222416,
+        "baseline_materialization_ms": 0.010917000000000001,
+        "static_graph_injection_ms": 0.003584,
+        "live_startup_ms": 0.0030410000000000003,
+        "first_result_latency_ms": 253.933375,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          253.933375
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 253.933375,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.007083,
+        "first_result_latency_ms": 254.56083299999997,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          254.56083299999997,
+          254.56412499999996,
+          254.564417
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.56083299999997,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.56412499999996,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.564417,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 1,
+        "historical_query_ms": 0.12904100000000002,
+        "baseline_materialization_ms": 0.0037500000000000003,
+        "static_graph_injection_ms": 0.002375,
+        "live_startup_ms": 0.002542,
+        "first_result_latency_ms": 250.94349999999997,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.94349999999997
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.94349999999997,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 1,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0047079999999999995,
+        "first_result_latency_ms": 255.06033299999999,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.06033299999999,
+          255.06400000000002,
+          255.06425
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06033299999999,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06400000000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06425,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 2,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_query_ms": 0.358416,
+        "baseline_materialization_ms": 0.011,
+        "static_graph_injection_ms": 0.007583,
+        "live_startup_ms": 0.006084,
+        "first_result_latency_ms": 254.978208,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          254.978208
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 254.978208,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.007416,
+        "first_result_latency_ms": 254.556542,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          254.556542,
+          254.56145800000002,
+          254.561708
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.556542,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.56145800000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 254.561708,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.42166599999998766
+    },
+    {
+      "run_index": 3,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 3,
+        "historical_query_ms": 0.267416,
+        "baseline_materialization_ms": 0.006125,
+        "static_graph_injection_ms": 0.0028339999999999997,
+        "live_startup_ms": 0.002,
+        "first_result_latency_ms": 255.025,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.025
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.025,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 3,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.007917,
+        "first_result_latency_ms": 251.208541,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          251.208541,
+          251.21412500000002,
+          251.214375
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.208541,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.21412500000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.214375,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 3.816459000000009
+    },
+    {
+      "run_index": 4,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 4,
+        "historical_query_ms": 0.184584,
+        "baseline_materialization_ms": 0.004834,
+        "static_graph_injection_ms": 0.0025,
+        "live_startup_ms": 0.033834,
+        "first_result_latency_ms": 254.34637500000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          254.34637500000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 254.34637500000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 4,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.008,
+        "first_result_latency_ms": 253.230167,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          253.230167,
+          253.23487500000002,
+          253.235084
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.230167,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.23487500000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.235084,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.025834000000000003,
+      "first_result_overhead_ms": 1.1162080000000287
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..c5517e5
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781261434353/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,6,1.000,0.267,0.011,0.004,0.003,254.587,255.025,253.969,254.587,255.025,1.000,1.000,1.000,,
+variant,smoke,live_only,6,1.000,,,,0.007,254.561,255.067,253.950,254.562,255.072,3.000,,,,
+comparison,smoke,comparison,6,,,,,,,,,,,,,0.000,0.422
diff --git a/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.raw.json
new file mode 100644
index 0000000..d6cdfe6
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.raw.json
@@ -0,0 +1,492 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 5",
+    "timestamp_unix_ms": 1781262452656
+  },
+  "profile": "smoke",
+  "runs": 5,
+  "warmup_runs": 1,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781262452588",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.551542,
+        "baseline_materialization_ms": 0.034499999999999996,
+        "static_graph_injection_ms": 0.017374999999999998,
+        "live_startup_ms": 0.0025830000000000002,
+        "first_result_latency_ms": 255.03262500000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.03262500000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.03262500000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
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+        "window_result_latencies_ms": [
+          255.056208,
+          255.06070800000003,
+          255.060958
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.056208,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06070800000003,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.060958,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
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+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.66100000000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.66100000000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
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+        "correctness_ok": true,
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+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          253.27624999999998,
+          253.28050000000002,
+          253.28075
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.27624999999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.28050000000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 253.28075,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
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+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 1,
+        "historical_query_ms": 0.24333300000000002,
+        "baseline_materialization_ms": 0.009583,
+        "static_graph_injection_ms": 0.003208,
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+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          253.312125
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 253.312125,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
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+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001959,
+        "first_result_latency_ms": 255.034875,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.034875,
+          255.038708,
+          255.03900000000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.034875,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.038708,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.03900000000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.001624,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 2,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_query_ms": 0.343709,
+        "baseline_materialization_ms": 0.012167,
+        "static_graph_injection_ms": 0.006333,
+        "live_startup_ms": 0.0067079999999999996,
+        "first_result_latency_ms": 250.27949999999998,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.27949999999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.27949999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.005917,
+        "first_result_latency_ms": 255.05879199999998,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.05879199999998,
+          255.064458,
+          255.06466700000001
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.05879199999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.064458,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06466700000001,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0007909999999999992,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 3,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 3,
+        "historical_query_ms": 0.3355,
+        "baseline_materialization_ms": 0.013083,
+        "static_graph_injection_ms": 0.005875,
+        "live_startup_ms": 0.017334,
+        "first_result_latency_ms": 252.308875,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          252.308875
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 252.308875,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 3,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.007125,
+        "first_result_latency_ms": 255.065042,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          255.065042,
+          255.06991699999998,
+          255.07029199999997
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.065042,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.06991699999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 255.07029199999997,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.010209,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "run_index": 4,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 4,
+        "historical_query_ms": 0.339333,
+        "baseline_materialization_ms": 0.010958,
+        "static_graph_injection_ms": 0.0067079999999999996,
+        "live_startup_ms": 0.006875,
+        "first_result_latency_ms": 250.24612499999998,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          250.24612499999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 250.24612499999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 4,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.003042,
+        "first_result_latency_ms": 250.11808299999998,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          250.11808299999998,
+          250.123583,
+          250.12379099999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.11808299999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.123583,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 250.12379099999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.003833,
+      "first_result_overhead_ms": 0.12804199999999355
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..0132ce1
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781262452588/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,6,1.000,0.339,0.012,0.006,0.007,252.309,255.033,251.973,252.309,255.033,1.000,1.000,1.000,,
+variant,smoke,live_only,6,1.000,,,,0.006,255.056,255.065,253.938,255.056,255.070,3.000,,,,
+comparison,smoke,comparison,6,,,,,,,,,,,,,0.002,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.raw.json
new file mode 100644
index 0000000..9fbdf18
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.raw.json
@@ -0,0 +1,97 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1",
+    "timestamp_unix_ms": 1781266934749
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781266934667",
+  "comparisons": [
+    {
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_query_ms": 0.5682499999999999,
+        "baseline_materialization_ms": 0.034749999999999996,
+        "static_graph_injection_ms": 0.021792000000000002,
+        "live_startup_ms": 0.0018750000000000001,
+        "first_result_latency_ms": 255.03329200000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          255.03329200000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 22.0,
+            "day_avg_value": 11.0,
+            "difference": 11.0,
+            "received_after_first_event_ms": 255.03329200000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 61020
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.00625,
+        "first_result_latency_ms": 251.296125,
+        "result_count": 3,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          251.296125,
+          251.300459,
+          251.300792
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.296125,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 21.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.300459,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 24.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 251.300792,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 3.737167000000028
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..91e4163
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781266934667/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+row_type,profile,variant,runs,correctness_rate,historical_query_ms_p50,baseline_materialization_ms_p50,static_graph_injection_ms_p50,live_startup_ms_p50,first_result_latency_ms_p50,first_result_latency_ms_p95,avg_window_result_latency_ms,p50_window_result_latency_ms,p95_window_result_latency_ms,avg_result_count,avg_materialized_quad_count,avg_baseline_binding_count,live_startup_overhead_ms_p50,first_result_overhead_ms_p50
+variant,smoke,baseline,1,1.000,0.568,0.035,0.022,0.002,255.033,255.033,255.033,255.033,255.033,1.000,1.000,1.000,,
+variant,smoke,live_only,1,1.000,,,,0.006,251.296,251.296,251.299,251.300,251.301,3.000,,,,
+comparison,smoke,comparison,1,,,,,,,,,,,,,0.000,3.737
diff --git a/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.raw.json
new file mode 100644
index 0000000..d3c1021
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.raw.json
@@ -0,0 +1,96 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1000 --baseline-entities 1 --verbose",
+    "timestamp_unix_ms": 1781270443990
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000
+  ],
+  "baseline_entities": [
+    1
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781270443919",
+  "comparisons": [
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.2715,
+        "materialization_ms": 0.013417,
+        "static_injection_ms": 0.009791,
+        "historical_query_ms": 1.2715,
+        "baseline_materialization_ms": 0.013417,
+        "static_graph_injection_ms": 0.009791,
+        "live_startup_ms": 0.002041,
+        "first_result_latency_ms": 30.037542000000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          30.037542000000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.037542000000002,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.00125,
+        "first_result_latency_ms": 30.034084,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.034084
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.034084,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0007909999999999998,
+      "first_result_overhead_ms": 0.0034580000000019595
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..c372f5c
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781270443919/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+profile,historical_events,baseline_entities,runs,warmup_runs,correctness_rate,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,baseline_binding_count_mean,baseline_binding_count_std,materialized_quad_count_mean,materialized_quad_count_std,baseline_result_count_mean,baseline_result_count_std,live_only_result_count_mean,live_only_result_count_std
+smoke,1000,1,1,0,1.000,1.272,0.000,0.013,0.000,0.010,0.000,30.038,0.000,30.034,0.000,0.001,0.000,0.003,0.000,1.000,0.000,1.000,0.000,1.000,0.000,1.000,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.raw.json
new file mode 100644
index 0000000..4dd7b36
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.raw.json
@@ -0,0 +1,2618 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 3 --historical-events 1000,10000 --baseline-entities 1,10",
+    "timestamp_unix_ms": 1781270449691
+  },
+  "profile": "smoke",
+  "runs": 3,
+  "warmup_runs": 1,
+  "historical_events": [
+    1000,
+    10000
+  ],
+  "baseline_entities": [
+    1,
+    10
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781270449631",
+  "comparisons": [
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": true,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.249458,
+        "materialization_ms": 0.011165999999999999,
+        "static_injection_ms": 0.010499999999999999,
+        "historical_query_ms": 1.249458,
+        "baseline_materialization_ms": 0.011165999999999999,
+        "static_graph_injection_ms": 0.010499999999999999,
+        "live_startup_ms": 0.001291,
+        "first_result_latency_ms": 30.021833,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          30.021833
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.021833,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.00125,
+        "first_result_latency_ms": 30.018957999999998,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.018957999999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.018957999999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00004100000000000002,
+      "first_result_overhead_ms": 0.0028750000000030695
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 0.989541,
+        "materialization_ms": 0.002458,
+        "static_injection_ms": 0.001458,
+        "historical_query_ms": 0.989541,
+        "baseline_materialization_ms": 0.002458,
+        "static_graph_injection_ms": 0.001458,
+        "live_startup_ms": 0.001,
+        "first_result_latency_ms": 30.020125,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          30.020125
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.020125,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001458,
+        "first_result_latency_ms": 30.016875,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.016875
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.016875,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0032500000000013074
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 1,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.386167,
+        "materialization_ms": 0.004209,
+        "static_injection_ms": 0.002,
+        "historical_query_ms": 1.386167,
+        "baseline_materialization_ms": 0.004209,
+        "static_graph_injection_ms": 0.002,
+        "live_startup_ms": 0.002125,
+        "first_result_latency_ms": 30.036459,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          30.036459
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.036459,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 1,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.005083000000000001,
+        "first_result_latency_ms": 29.165625000000002,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          29.165625000000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.165625000000002,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.8708339999999986
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 2,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 3.536666,
+        "materialization_ms": 0.010499999999999999,
+        "static_injection_ms": 0.0043749999999999995,
+        "historical_query_ms": 3.536666,
+        "baseline_materialization_ms": 0.010499999999999999,
+        "static_graph_injection_ms": 0.0043749999999999995,
+        "live_startup_ms": 0.004459,
+        "first_result_latency_ms": 25.138709,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          25.138709
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 25.138709,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.005083000000000001,
+        "first_result_latency_ms": 30.081792,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.081792
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.081792,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 10,
+      "is_warmup": true,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 10,
+        "baseline_eval_ms": 2.4205419999999997,
+        "materialization_ms": 0.022917,
+        "static_injection_ms": 0.025459000000000002,
+        "historical_query_ms": 2.4205419999999997,
+        "baseline_materialization_ms": 0.022917,
+        "static_graph_injection_ms": 0.025459000000000002,
+        "live_startup_ms": 0.003875,
+        "first_result_latency_ms": 26.659,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          26.659,
+          26.661084000000002,
+          26.662417,
+          26.660792,
+          26.661167,
+          26.661250000000003,
+          26.662542000000002,
+          26.662292,
+          26.663084,
+          26.662459
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 26.659,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 26.661084000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 26.662417,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 26.660792,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 26.661167,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 26.661250000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 26.662542000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 26.662292,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 26.663084,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 26.662459,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 10,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0038330000000000005,
+        "first_result_latency_ms": 30.052916999999997,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.052916999999997,
+          30.054542,
+          30.054707999999998,
+          30.057875000000003,
+          30.054375,
+          30.054875000000003,
+          30.05675,
+          30.056583,
+          30.056917,
+          30.057083
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.052916999999997,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.054542,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.054707999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.057875000000003,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.054375,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.054875000000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.05675,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.056583,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.056917,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
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+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 25.288874999999997,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 25.291125,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 25.291459,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 4.766749000000001
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..144d4ed
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781270449631/query_defined_baseline.summary.csv
@@ -0,0 +1,5 @@
+profile,historical_events,baseline_entities,runs,warmup_runs,correctness_rate,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,baseline_binding_count_mean,baseline_binding_count_std,materialized_quad_count_mean,materialized_quad_count_std,baseline_result_count_mean,baseline_result_count_std,live_only_result_count_mean,live_only_result_count_std
+smoke,1000,1,3,1,1.000,1.971,1.371,0.006,0.004,0.003,0.002,28.398,2.823,29.755,0.511,0.000,0.000,0.291,0.502,1.000,0.000,1.000,0.000,1.000,0.000,1.000,0.000
+smoke,1000,10,3,1,1.000,1.972,1.159,0.018,0.008,0.015,0.007,28.259,2.059,30.042,0.024,0.000,0.001,0.003,0.006,10.000,0.000,10.000,0.000,10.000,0.000,10.000,0.000
+smoke,10000,1,3,1,1.000,12.643,3.179,0.003,0.001,0.002,0.000,30.020,0.004,30.033,0.012,0.000,0.000,0.000,0.000,1.000,0.000,1.000,0.000,1.000,0.000,1.000,0.000
+smoke,10000,10,3,1,1.000,13.933,2.528,0.012,0.001,0.011,0.001,30.040,0.011,28.475,2.761,0.000,0.000,1.589,2.752,10.000,0.000,10.000,0.000,10.000,0.000,10.000,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.raw.json
new file mode 100644
index 0000000..5060cf8
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.raw.json
@@ -0,0 +1,2618 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 3 --historical-events 1000,10000 --baseline-entities 1,10",
+    "timestamp_unix_ms": 1781272016698
+  },
+  "profile": "smoke",
+  "runs": 3,
+  "warmup_runs": 1,
+  "historical_events": [
+    1000,
+    10000
+  ],
+  "baseline_entities": [
+    1,
+    10
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781272016618",
+  "comparisons": [
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": true,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.251083,
+        "materialization_ms": 0.019375,
+        "static_injection_ms": 0.001375,
+        "historical_query_ms": 1.251083,
+        "baseline_materialization_ms": 0.019375,
+        "static_graph_injection_ms": 0.001375,
+        "live_startup_ms": 0.00275,
+        "first_result_latency_ms": 27.498541000000003,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          27.498541000000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 27.498541000000003,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.002959,
+        "first_result_latency_ms": 28.605042,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          28.605042
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 28.605042,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 0.9522079999999999,
+        "materialization_ms": 0.003292,
+        "static_injection_ms": 0.0018750000000000001,
+        "historical_query_ms": 0.9522079999999999,
+        "baseline_materialization_ms": 0.003292,
+        "static_graph_injection_ms": 0.0018750000000000001,
+        "live_startup_ms": 0.001625,
+        "first_result_latency_ms": 25.832209,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          25.832209
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 25.832209,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001792,
+        "first_result_latency_ms": 30.023708,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.023708
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023708,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 1,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.454459,
+        "materialization_ms": 0.004333,
+        "static_injection_ms": 0.002458,
+        "historical_query_ms": 1.454459,
+        "baseline_materialization_ms": 0.004333,
+        "static_graph_injection_ms": 0.002458,
+        "live_startup_ms": 0.001708,
+        "first_result_latency_ms": 30.026625000000003,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          30.026625000000003
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.026625000000003,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 1,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.002,
+        "first_result_latency_ms": 30.03375,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.03375
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.03375,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 1,
+      "is_warmup": false,
+      "run_index": 2,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": 1.653459,
+        "materialization_ms": 0.007875,
+        "static_injection_ms": 0.0043749999999999995,
+        "historical_query_ms": 1.653459,
+        "baseline_materialization_ms": 0.007875,
+        "static_graph_injection_ms": 0.0043749999999999995,
+        "live_startup_ms": 0.0036669999999999997,
+        "first_result_latency_ms": 27.92275,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": 1,
+        "baseline_binding_count": 1,
+        "window_result_latencies_ms": [
+          27.92275
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 27.92275,
+            "timestamp_from": 1000,
+            "timestamp_to": 61000
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_events": 1000,
+        "baseline_entities": 1,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.005208999999999999,
+        "first_result_latency_ms": 26.893167,
+        "result_count": 1,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          26.893167
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 26.893167,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 1.0295830000000024
+    },
+    {
+      "historical_events": 1000,
+      "baseline_entities": 10,
+      "is_warmup": true,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 10,
+        "baseline_eval_ms": 1.6015840000000001,
+        "materialization_ms": 0.01925,
+        "static_injection_ms": 0.021333,
+        "historical_query_ms": 1.6015840000000001,
+        "baseline_materialization_ms": 0.01925,
+        "static_graph_injection_ms": 0.021333,
+        "live_startup_ms": 0.0041659999999999996,
+        "first_result_latency_ms": 25.934042,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          25.934042,
+          25.934375,
+          25.93625,
+          25.937708,
+          25.934583,
+          25.93475,
+          25.93675,
+          25.936417,
+          25.932083000000002,
+          25.936583
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 25.934042,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 25.934375,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 25.93625,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 25.937708,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 25.934583,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 25.93475,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 25.93675,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 25.936417,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 25.932083000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 25.936583,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000,
+        "baseline_entities": 10,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0055,
+        "first_result_latency_ms": 27.051542,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          27.051542,
+          27.055374999999998,
+          27.058834,
+          27.060417,
+          27.055,
+          27.055625,
+          27.059041999999998,
+          27.0555,
+          27.058959,
+          27.059167
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.051542,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.055374999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.058834,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.060417,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.055,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.055625,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.059041999999998,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.0555,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.058959,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 27.059167,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
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+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023125,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023833,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024208,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00008299999999999996,
+      "first_result_overhead_ms": 0.0023330000000001405
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..04adbc8
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline.summary.csv
@@ -0,0 +1,5 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std
+1000,1,3,1,1.000,1.000,1.000,1.000,1.000,1.353,0.361,0.005,0.002,0.003,0.001,27.927,2.097,28.984,1.810,0.000,0.000,0.343,0.594
+1000,10,3,1,1.000,10.000,10.000,10.000,10.000,2.599,0.319,0.025,0.001,0.024,0.002,26.771,1.406,27.933,1.900,0.000,0.000,0.148,0.256
+10000,1,3,1,1.000,1.000,1.000,1.000,1.000,7.094,0.987,0.004,0.000,0.002,0.000,28.471,2.698,29.897,0.216,0.000,0.000,0.005,0.008
+10000,10,3,1,1.000,10.000,10.000,10.000,10.000,7.180,1.136,0.008,0.001,0.006,0.001,30.024,0.003,30.018,0.004,0.000,0.000,0.006,0.005
diff --git a/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline_results.md
new file mode 100644
index 0000000..7befade
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272016618/query_defined_baseline_results.md
@@ -0,0 +1,6 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000 | 1 | 1 | 1.353 ± 0.361 | 0.005 ± 0.002 | 0.003 ± 0.001 | 0.343 ± 0.594 | 1.000 |
+| 1000 | 10 | 10 | 2.599 ± 0.319 | 0.025 ± 0.001 | 0.024 ± 0.002 | 0.148 ± 0.256 | 1.000 |
+| 10000 | 1 | 1 | 7.094 ± 0.987 | 0.004 ± 0.000 | 0.002 ± 0.000 | 0.005 ± 0.008 | 1.000 |
+| 10000 | 10 | 10 | 7.180 ± 1.136 | 0.008 ± 0.001 | 0.006 ± 0.001 | 0.006 ± 0.005 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.raw.json
new file mode 100644
index 0000000..4bbd6e5
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.raw.json
@@ -0,0 +1,280 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1000000 --baseline-entities 10",
+    "timestamp_unix_ms": 1781272847134
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781272847058",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 254.3969129965406,
+        "storage_write_ms": 92.27154099992191,
+        "baseline_eval_ms": 668.871542,
+        "materialization_ms": 0.133,
+        "static_injection_ms": 0.009042000000000001,
+        "historical_query_ms": 668.871542,
+        "baseline_materialization_ms": 0.133,
+        "static_graph_injection_ms": 0.009042000000000001,
+        "live_startup_ms": 0.0028339999999999997,
+        "first_result_latency_ms": 25.368792000000003,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          25.368792000000003,
+          25.369084,
+          25.373167,
+          25.375459,
+          25.369292,
+          25.3695,
+          25.37375,
+          25.373375,
+          25.362541999999998,
+          25.373542
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 25.368792000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 25.369084,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 25.373167,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 25.375459,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 25.369292,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 25.3695,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 25.37375,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 25.373375,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 25.362541999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 25.373542,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 254.3969129965406,
+        "storage_write_ms": 92.27154099992191,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.002,
+        "first_result_latency_ms": 29.644582999999997,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          29.644582999999997,
+          29.649625,
+          29.649874999999998,
+          29.653791,
+          29.649416000000002,
+          29.650040999999998,
+          29.654166,
+          29.653083,
+          29.655708,
+          29.653958
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.644582999999997,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.649625,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.649874999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.653791,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.649416000000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.650040999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.654166,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.653083,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.655708,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.653958,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0008339999999999997,
+      "first_result_overhead_ms": 0.0
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..574e11b
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+1000000,10,1,0,1.000,10.000,10.000,10.000,10.000,668.872,0.000,0.133,0.000,0.009,0.000,25.369,0.000,29.645,0.000,0.001,0.000,0.000,0.000,254.397,0.000,92.272,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline_results.md
new file mode 100644
index 0000000..0e75aae
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272847058/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 10 | 668.872 ± 0.000 | 0.133 ± 0.000 | 0.009 ± 0.000 | 0.000 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.raw.json
new file mode 100644
index 0000000..55af727
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.raw.json
@@ -0,0 +1,280 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 5000000 --baseline-entities 10",
+    "timestamp_unix_ms": 1781272889242
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    5000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781272889174",
+  "comparisons": [
+    {
+      "historical_events": 5000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 5000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 1402.629495992737,
+        "storage_write_ms": 437.1827360210969,
+        "baseline_eval_ms": 4627.503333,
+        "materialization_ms": 0.24808399999999997,
+        "static_injection_ms": 0.011792,
+        "historical_query_ms": 4627.503333,
+        "baseline_materialization_ms": 0.24808399999999997,
+        "static_graph_injection_ms": 0.011792,
+        "live_startup_ms": 0.003625,
+        "first_result_latency_ms": 30.033583,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.033583,
+          30.033791,
+          30.035249999999998,
+          30.032375000000002,
+          30.034000000000002,
+          30.034208,
+          30.035708,
+          30.035041,
+          30.042208000000002,
+          30.035415999999998
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.033583,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.033791,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.035249999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.032375000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.034000000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.034208,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.035708,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.035041,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.042208000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.035415999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 5000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 1402.629495992737,
+        "storage_write_ms": 437.1827360210969,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001083,
+        "first_result_latency_ms": 30.027417,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.027417,
+          30.028458,
+          30.028667,
+          30.029833,
+          30.02825,
+          30.029083,
+          30.030041999999998,
+          30.029625,
+          30.030542,
+          30.030208
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.027417,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.028458,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.028667,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029833,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02825,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029083,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030041999999998,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029625,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030542,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030208,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.002542,
+      "first_result_overhead_ms": 0.006166000000000338
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..dbd908d
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+5000000,10,1,0,1.000,10.000,10.000,10.000,10.000,4627.503,0.000,0.248,0.000,0.012,0.000,30.034,0.000,30.027,0.000,0.003,0.000,0.006,0.000,1402.629,0.000,437.183,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline_results.md
new file mode 100644
index 0000000..b27d0ee
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272889174/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 5000000 | 10 | 10 | 4627.503 ± 0.000 | 0.248 ± 0.000 | 0.012 ± 0.000 | 0.006 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.raw.json
new file mode 100644
index 0000000..85af7e6
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.raw.json
@@ -0,0 +1,280 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 10000000 --baseline-entities 10",
+    "timestamp_unix_ms": 1781272899477
+  },
+  "profile": "smoke",
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    10000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "output_dir": "logs/benchmark/query_defined_baseline/1781272899410",
+  "comparisons": [
+    {
+      "historical_events": 10000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 2502.5689833101883,
+        "storage_write_ms": 895.056996111171,
+        "baseline_eval_ms": 9354.206583,
+        "materialization_ms": 0.52825,
+        "static_injection_ms": 0.011458,
+        "historical_query_ms": 9354.206583,
+        "baseline_materialization_ms": 0.52825,
+        "static_graph_injection_ms": 0.011458,
+        "live_startup_ms": 0.002208,
+        "first_result_latency_ms": 30.0415,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.0415,
+          30.043208,
+          30.045125,
+          30.046458,
+          30.04325,
+          30.043291,
+          30.045208,
+          30.045083,
+          30.043166,
+          30.045166000000002
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.0415,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.043208,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.045125,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.046458,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.04325,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.043291,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.045208,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.045083,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.043166,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.045166000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "historical_generation_ms": 2502.5689833101883,
+        "storage_write_ms": 895.056996111171,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.002667,
+        "first_result_latency_ms": 30.024542,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.024542,
+          30.025709000000003,
+          30.026500000000002,
+          30.027084,
+          30.025625,
+          30.025792,
+          30.026709,
+          30.02575,
+          30.026625000000003,
+          30.026584
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024542,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025709000000003,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026500000000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.027084,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025625,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025792,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026709,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02575,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026625000000003,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026584,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.01695799999999892
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..bfd95ee
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+10000000,10,1,0,1.000,10.000,10.000,10.000,10.000,9354.207,0.000,0.528,0.000,0.011,0.000,30.041,0.000,30.025,0.000,0.000,0.000,0.017,0.000,2502.569,0.000,895.057,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline_results.md
new file mode 100644
index 0000000..fa061e4
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781272899410/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 10000000 | 10 | 10 | 9354.207 ± 0.000 | 0.528 ± 0.000 | 0.011 ± 0.000 | 0.017 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.raw.json
new file mode 100644
index 0000000..ed42f3c
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.raw.json
@@ -0,0 +1,104 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 10000 --baseline-entities 10 --live-replay-mode realtime --live-rate-hz 4 --live-duration-seconds 130 --live-window-size-seconds 120 --live-window-slide-seconds 60",
+    "timestamp_unix_ms": 1781274083525
+  },
+  "profile": "smoke",
+  "live_replay_mode": "realtime",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": 130,
+  "live_window_size_seconds": 120,
+  "live_window_slide_seconds": 60,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    10000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": false,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781274083449",
+  "comparisons": [
+    {
+      "historical_events": 10000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 130,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 520,
+        "expected_completed_windows": 1,
+        "observed_completed_windows": 0,
+        "window_semantics_note": "Ignored 30 flush-window rows beyond the logical replay horizon because the close_stream sentinel finalized windows past 130s. Observed 0 completed windows vs expected 1; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.658230999999842,
+        "storage_write_ms": 1.0524260000001262,
+        "baseline_eval_ms": 7.061584,
+        "materialization_ms": 0.035667000000000004,
+        "static_injection_ms": 0.006667,
+        "historical_query_ms": 7.061584,
+        "baseline_materialization_ms": 0.035667000000000004,
+        "static_graph_injection_ms": 0.006667,
+        "live_startup_ms": 0.002125,
+        "first_result_latency_ms": 0.0,
+        "result_count": 0,
+        "correctness_ok": false,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [],
+        "completed_window_latencies_ms": [],
+        "completed_window_result_counts": [],
+        "observed_rows": []
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 130,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 520,
+        "expected_completed_windows": 1,
+        "observed_completed_windows": 0,
+        "window_semantics_note": "Ignored 30 flush-window rows beyond the logical replay horizon because the close_stream sentinel finalized windows past 130s. Observed 0 completed windows vs expected 1; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.658230999999842,
+        "storage_write_ms": 1.0524260000001262,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.005167,
+        "first_result_latency_ms": 0.0,
+        "result_count": 0,
+        "correctness_ok": false,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [],
+        "completed_window_latencies_ms": [],
+        "completed_window_result_counts": [],
+        "observed_rows": []
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..5041a60
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+10000,10,1,0,0.000,10.000,10.000,0.000,0.000,7.062,0.000,0.036,0.000,0.007,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,2.658,0.000,1.052,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline_results.md
new file mode 100644
index 0000000..a451f08
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274083449/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 10000 | 10 | 10 | 7.062 ± 0.000 | 0.036 ± 0.000 | 0.007 ± 0.000 | 0.000 ± 0.000 | 0.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.raw.json
new file mode 100644
index 0000000..1e6ac5f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.raw.json
@@ -0,0 +1,724 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 10000 --baseline-entities 10 --live-replay-mode realtime --live-rate-hz 4 --live-duration-seconds 130 --live-window-size-seconds 120 --live-window-slide-seconds 60",
+    "timestamp_unix_ms": 1781274460893
+  },
+  "profile": "smoke",
+  "live_replay_mode": "realtime",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": 130,
+  "live_window_size_seconds": 120,
+  "live_window_slide_seconds": 60,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    10000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": false,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781274460814",
+  "comparisons": [
+    {
+      "historical_events": 10000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 130,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 520,
+        "expected_completed_windows": 1,
+        "observed_completed_windows": 3,
+        "window_semantics_note": "Observed 3 completed windows vs expected 1; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.512927999999971,
+        "storage_write_ms": 0.9053090000001016,
+        "baseline_eval_ms": 6.706875,
+        "materialization_ms": 0.032292,
+        "static_injection_ms": 0.006291000000000001,
+        "historical_query_ms": 6.706875,
+        "baseline_materialization_ms": 0.032292,
+        "static_graph_injection_ms": 0.006291000000000001,
+        "live_startup_ms": 0.001625,
+        "first_result_latency_ms": 60503.022541,
+        "result_count": 30,
+        "correctness_ok": false,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
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+          60503.022666,
+          60503.026416,
+          60503.048416,
+          60503.022875,
+          60503.022958,
+          60503.026625,
+          60503.026290999995,
+          60503.02025,
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+          120505.101458,
+          120505.102,
+          120505.105416,
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+          120505.101833,
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+          129756.83829100001,
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+          129756.838208,
+          129756.83804100001,
+          129756.83520800002,
+          129756.838166
+        ],
+        "completed_window_latencies_ms": [
+          60503.02025,
+          120505.07791600001,
+          129756.83520800002
+        ],
+        "completed_window_result_counts": [
+          10,
+          10,
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 60503.022541,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 60503.022666,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 60503.026416,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 60503.048416,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 60503.022875,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 60503.022958,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 60503.026625,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 60503.026290999995,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 60503.02025,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 60503.0265,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 120505.101375,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 120505.101458,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 120505.102,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 120505.105416,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 120505.10175,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 120505.101833,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 120505.105333,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 120505.101916,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 120505.07791600001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 120505.10525,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 129756.83758299999,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 129756.837625,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 129756.838083,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 129756.83829100001,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 129756.837708,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 129756.837833,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 129756.838208,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 129756.83804100001,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 129756.83520800002,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 129756.838166,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 130,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 520,
+        "expected_completed_windows": 1,
+        "observed_completed_windows": 3,
+        "window_semantics_note": "Observed 3 completed windows vs expected 1; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.512927999999971,
+        "storage_write_ms": 0.9053090000001016,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0053750000000000004,
+        "first_result_latency_ms": 60500.831292,
+        "result_count": 30,
+        "correctness_ok": false,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
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+          60500.831333,
+          60500.831208,
+          60500.828917,
+          60500.831417,
+          60500.828833,
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+          60500.828708,
+          60500.827375,
+          60500.857125,
+          120500.829958,
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+          120500.82991700001,
+          120500.83170800001,
+          120500.829833,
+          120500.82974999999,
+          120500.829667,
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+          120500.83175,
+          129761.35045800002,
+          129761.35083299999,
+          129761.350292,
+          129761.35016699998,
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+          129761.34999999999,
+          129761.34954200001,
+          129761.34987500001,
+          129761.348792,
+          129761.35070800001
+        ],
+        "completed_window_latencies_ms": [
+          60500.827375,
+          120500.82929200001,
+          129761.348792
+        ],
+        "completed_window_result_counts": [
+          10,
+          10,
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.831292,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.831333,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.831208,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.828917,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.831417,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.828833,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.828624999995,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.828708,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.827375,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60500.857125,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.829958,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.830042,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.831833,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.82991700001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.83170800001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.829833,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.82974999999,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.829667,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.82929200001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120500.83175,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.35045800002,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.35083299999,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.350292,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.35016699998,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.35058299999,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.34999999999,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.34954200001,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.34987500001,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.348792,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 129761.35070800001,
+            "timestamp_from": 1900000129750,
+            "timestamp_to": 1900000249750
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 2.191248999995878
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..c6ee3af
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+10000,10,1,0,0.000,10.000,10.000,30.000,30.000,6.707,0.000,0.032,0.000,0.006,0.000,60503.023,0.000,60500.831,0.000,0.000,0.000,2.191,0.000,2.513,0.000,0.905,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline_results.md
new file mode 100644
index 0000000..d9ea4a4
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274460814/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 10000 | 10 | 10 | 6.707 ± 0.000 | 0.032 ± 0.000 | 0.006 ± 0.000 | 2.191 ± 0.000 | 0.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.raw.json
new file mode 100644
index 0000000..5fa4c67
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.raw.json
@@ -0,0 +1,928 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 10000 --baseline-entities 10 --live-replay-mode realtime --live-rate-hz 4 --live-duration-seconds 240 --live-window-size-seconds 120 --live-window-slide-seconds 60",
+    "timestamp_unix_ms": 1781274737077
+  },
+  "profile": "smoke",
+  "live_replay_mode": "realtime",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": 240,
+  "live_window_size_seconds": 120,
+  "live_window_slide_seconds": 60,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    10000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": false,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781274737022",
+  "comparisons": [
+    {
+      "historical_events": 10000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 240,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 960,
+        "expected_completed_windows": 3,
+        "observed_completed_windows": 4,
+        "window_semantics_note": "Observed 4 completed windows vs expected 3; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.620901999999921,
+        "storage_write_ms": 1.0058210000001218,
+        "baseline_eval_ms": 6.9632499999999995,
+        "materialization_ms": 0.036459,
+        "static_injection_ms": 0.007708,
+        "historical_query_ms": 6.9632499999999995,
+        "baseline_materialization_ms": 0.036459,
+        "static_graph_injection_ms": 0.007708,
+        "live_startup_ms": 0.001625,
+        "first_result_latency_ms": 60502.258458,
+        "result_count": 40,
+        "correctness_ok": false,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          60502.258458,
+          60502.260665999995,
+          60502.263583,
+          60502.260540999996,
+          60502.260875,
+          60502.260916,
+          60502.26375,
+          60502.263541,
+          60502.269916000005,
+          60502.263625,
+          120505.058166,
+          120505.058875,
+          120505.05925,
+          120505.058833,
+          120505.05895800001,
+          120505.05916599999,
+          120505.063541,
+          120505.059208,
+          120505.06362500001,
+          120505.0635,
+          180503.670416,
+          180503.671333,
+          180503.67204099998,
+          180503.671041,
+          180503.6715,
+          180503.67162500002,
+          180503.67225,
+          180503.671916,
+          180503.672375,
+          180503.672125,
+          239757.466416,
+          239757.467125,
+          239757.491916,
+          239757.466916,
+          239757.491541,
+          239757.491666,
+          239757.49216599998,
+          239757.49175000002,
+          239757.492291,
+          239757.49204100002
+        ],
+        "completed_window_latencies_ms": [
+          60502.258458,
+          120505.058166,
+          180503.670416,
+          239757.466416
+        ],
+        "completed_window_result_counts": [
+          10,
+          10,
+          10,
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 60502.258458,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 60502.260665999995,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 60502.263583,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 60502.260540999996,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 60502.260875,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 60502.260916,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 60502.26375,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 60502.263541,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 60502.269916000005,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 60502.263625,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 120505.058166,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 120505.058875,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 120505.05925,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 120505.058833,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 120505.05895800001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 120505.05916599999,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 120505.063541,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 120505.059208,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 120505.06362500001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 120505.0635,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 180503.670416,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 180503.671333,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 180503.67204099998,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 180503.671041,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 180503.6715,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 180503.67162500002,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 180503.67225,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 180503.671916,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 180503.672375,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 180503.672125,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 239757.466416,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 239757.467125,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 239757.491916,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 239757.466916,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 239757.491541,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 239757.491666,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 239757.49216599998,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 239757.49175000002,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 239757.492291,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 239757.49204100002,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 240,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 960,
+        "expected_completed_windows": 3,
+        "observed_completed_windows": 4,
+        "window_semantics_note": "Observed 4 completed windows vs expected 3; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+        "historical_generation_ms": 2.620901999999921,
+        "storage_write_ms": 1.0058210000001218,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.006375,
+        "first_result_latency_ms": 60503.707875,
+        "result_count": 40,
+        "correctness_ok": false,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          60503.707875,
+          60503.703125,
+          60503.705833,
+          60503.70575,
+          60503.705958,
+          60503.703,
+          60503.7025,
+          60503.702667,
+          60503.700583,
+          60503.706083,
+          120505.03775,
+          120505.037625,
+          120505.037708,
+          120505.039333,
+          120505.039208,
+          120505.037583,
+          120505.037417,
+          120505.0375,
+          120505.036875,
+          120505.039292,
+          180501.497,
+          180501.496667,
+          180501.496833,
+          180501.497458,
+          180501.497125,
+          180501.4965,
+          180501.49633300002,
+          180501.496167,
+          180501.495542,
+          180501.49729200001,
+          239758.295583,
+          239758.295167,
+          239758.295,
+          239758.294875,
+          239758.29529200002,
+          239758.294708,
+          239758.29175,
+          239758.291875,
+          239758.291292,
+          239758.295417
+        ],
+        "completed_window_latencies_ms": [
+          60503.700583,
+          120505.036875,
+          180501.495542,
+          239758.291292
+        ],
+        "completed_window_result_counts": [
+          10,
+          10,
+          10,
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.707875,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.703125,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.705833,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.70575,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.705958,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.703,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.7025,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.702667,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.700583,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 60503.706083,
+            "timestamp_from": 1900000059750,
+            "timestamp_to": 1900000179750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.03775,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.037625,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.037708,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.039333,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.039208,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.037583,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.037417,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.0375,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.036875,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.039292,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.497,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.496667,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.496833,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.497458,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.497125,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.4965,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.49633300002,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.496167,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.495542,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180501.49729200001,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.295583,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.295167,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.295,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.294875,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.29529200002,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.294708,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.29175,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.291875,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.291292,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239758.295417,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..fdddf62
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+10000,10,1,0,0.000,10.000,10.000,40.000,40.000,6.963,0.000,0.036,0.000,0.008,0.000,60502.258,0.000,60503.708,0.000,0.000,0.000,0.000,0.000,2.621,0.000,1.006,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline_results.md
new file mode 100644
index 0000000..4b99cc3
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781274737022/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 10000 | 10 | 10 | 6.963 ± 0.000 | 0.036 ± 0.000 | 0.008 ± 0.000 | 0.000 ± 0.000 | 0.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.raw.json
new file mode 100644
index 0000000..421ee0c
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.raw.json
@@ -0,0 +1,934 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 10000 --baseline-entities 10 --live-replay-mode realtime --live-rate-hz 4 --live-duration-seconds 240 --live-window-size-seconds 120 --live-window-slide-seconds 60",
+    "timestamp_unix_ms": 1781276063711
+  },
+  "profile": "smoke",
+  "live_replay_mode": "realtime",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": 240,
+  "live_window_size_seconds": 120,
+  "live_window_slide_seconds": 60,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    10000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781276063633",
+  "comparisons": [
+    {
+      "historical_events": 10000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 40,
+      "observed_live_only_rows": 40,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000,
+        "baseline_entities": 10,
+        "live_replay_mode": "realtime",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": 240,
+        "live_window_size_seconds": 120,
+        "live_window_slide_seconds": 60,
+        "live_event_count": 960,
+        "expected_emitted_windows": 4,
+        "expected_full_windows": 3,
+        "warmup_window_count": 1,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": "Realtime replay reports emitted windows separately from full windows; the first emission is the initial warm-up window and full windows follow at the logical duration horizon.",
+        "historical_generation_ms": 2.581153999999929,
+        "storage_write_ms": 1.0196140000001324,
+        "baseline_eval_ms": 6.997458,
+        "materialization_ms": 0.035250000000000004,
+        "static_injection_ms": 0.017959,
+        "historical_query_ms": 6.997458,
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+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.104833,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.104625,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.1045,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.10370800001,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 120505.108416,
+            "timestamp_from": 1900000119750,
+            "timestamp_to": 1900000239750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.274375,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.274833,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.2745,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.27425,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.274583,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.27412500003,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.27362499997,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.274,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.27254099998,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 180502.27470799998,
+            "timestamp_from": 1900000179750,
+            "timestamp_to": 1900000299750
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.134583,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.134458,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.134708,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.134916,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.134791,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.13433300002,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.13150000002,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.131625,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.131208,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 239757.135041,
+            "timestamp_from": 1900000239750,
+            "timestamp_to": 1900000359750
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.0
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..84e638f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std
+10000,10,1,0,1.000,4.000,3.000,1.000,4.000,0.000,40.000,0.000,40.000,0.000,10.000,10.000,40.000,40.000,6.997,0.000,0.035,0.000,0.018,0.000,60500.271,0.000,60501.982,0.000,0.000,0.000,0.000,0.000,2.581,0.000,1.020,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline_results.md
new file mode 100644
index 0000000..f0f2ba6
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781276063633/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 10000 | 10 | 4.000 | 3.000 | 1.000 | 4.000 | 40.000 | 40.000 | 10 | 6.997 ± 0.000 | 0.035 ± 0.000 | 0.018 ± 0.000 | 0.000 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.raw.json
new file mode 100644
index 0000000..291df0d
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.raw.json
@@ -0,0 +1,971 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1M,5M,10M --baseline-entities 10",
+    "timestamp_unix_ms": 1781285296297
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000,
+    5000000,
+    10000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": false,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781285296228",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 251.07944499644856,
+        "storage_write_ms": 90.50320999992455,
+        "baseline_eval_ms": 666.449042,
+        "materialization_ms": 0.07125,
+        "static_injection_ms": 0.009292,
+        "historical_query_ms": 666.449042,
+        "baseline_materialization_ms": 0.07125,
+        "static_graph_injection_ms": 0.009292,
+        "live_startup_ms": 0.002791,
+        "first_result_latency_ms": 30.044207999999998,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.044207999999998,
+          30.046125,
+          30.047541,
+          30.045916,
+          30.046333,
+          30.046541,
+          30.047958,
+          30.047291,
+          30.048499999999997,
+          30.04775
+        ],
+        "completed_window_latencies_ms": [
+          30.044207999999998
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.044207999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.046125,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.047541,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.045916,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.046333,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.046541,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.047958,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.047291,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.048499999999997,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.04775,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 251.07944499644856,
+        "storage_write_ms": 90.50320999992455,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.000959,
+        "first_result_latency_ms": 30.024834,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": false,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.024834,
+          30.026958999999998,
+          30.026792,
+          30.029459000000003,
+          30.02725,
+          30.027167000000002,
+          30.030874999999998,
+          30.029875,
+          30.029584,
+          30.029667
+        ],
+        "completed_window_latencies_ms": [
+          30.024834,
+          30.026792,
+          30.027167000000002,
+          30.029584
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024834,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026958999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026792,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029459000000003,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02725,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.027167000000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030874999999998,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029875,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029584,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029667,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.001832,
+      "first_result_overhead_ms": 0.019373999999999114,
+      "peak_rss_mb": 605.25,
+      "mean_rss_mb": 485.375,
+      "peak_cpu_percent": 100.76897430419922,
+      "mean_cpu_percent": 100.14065551757812,
+      "sample_count": 2
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+          30.030583
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+          10
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+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
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+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.032125,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
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+          {
+            "sensor": "http://example.org/sensor1",
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+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.03225,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
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+          {
+            "sensor": "http://example.org/sensor2",
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+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.033375,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
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+          {
+            "sensor": "http://example.org/sensor3",
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+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.03425,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
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+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.032291,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
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+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.032375000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.033541,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.033416,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.030583,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.0335,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
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+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 5000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
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+        "materialization_ms": null,
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+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001542,
+        "first_result_latency_ms": 30.020125,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": false,
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+        "window_result_latencies_ms": [
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+          30.021875,
+          30.021791999999998,
+          30.021917,
+          30.021958,
+          30.023042,
+          30.02375,
+          30.023083,
+          30.023125,
+          30.023167
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+        "completed_window_latencies_ms": [
+          30.020125,
+          30.021791999999998,
+          30.021917,
+          30.023083
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.020125,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021875,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021791999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
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+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021917,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
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+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021958,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023042,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
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+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02375,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
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+            "difference": null,
+            "received_after_first_event_ms": 30.023083,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
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+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023125,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023167,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00008299999999999996,
+      "first_result_overhead_ms": 0.012000000000000455,
+      "peak_rss_mb": 2656.359375,
+      "mean_rss_mb": 2022.955078125,
+      "peak_cpu_percent": 101.70673370361328,
+      "mean_cpu_percent": 92.05566835403442,
+      "sample_count": 16
+    },
+    {
+      "historical_events": 10000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
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+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 2532.608043285927,
+        "storage_write_ms": 843.8229821025088,
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+        "materialization_ms": 0.41645899999999997,
+        "static_injection_ms": 0.010667,
+        "historical_query_ms": 9329.223625,
+        "baseline_materialization_ms": 0.41645899999999997,
+        "static_graph_injection_ms": 0.010667,
+        "live_startup_ms": 0.0052499999999999995,
+        "first_result_latency_ms": 30.039292,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
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+          30.040792,
+          30.042084,
+          30.043042,
+          30.041,
+          30.041209,
+          30.042666999999998,
+          30.042292000000003,
+          30.040584,
+          30.042459
+        ],
+        "completed_window_latencies_ms": [
+          30.039292
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.039292,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.040792,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.042084,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.043042,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.041,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.041209,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.042666999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.042292000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.040584,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.042459,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 2532.608043285927,
+        "storage_write_ms": 843.8229821025088,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.00125,
+        "first_result_latency_ms": 30.02225,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": false,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.02225,
+          30.023292,
+          30.023083,
+          30.023500000000002,
+          30.023708,
+          30.024458,
+          30.024625,
+          30.024833,
+          30.025458,
+          30.025042
+        ],
+        "completed_window_latencies_ms": [
+          30.02225,
+          30.023083,
+          30.023500000000002,
+          30.024625
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02225,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023292,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023083,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023500000000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023708,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024458,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024625,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024833,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025458,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025042,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.003999999999999999,
+      "first_result_overhead_ms": 0.017042,
+      "peak_rss_mb": 4143.890625,
+      "mean_rss_mb": 3433.150760135135,
+      "peak_cpu_percent": 101.12734985351562,
+      "mean_cpu_percent": 83.00561100727803,
+      "sample_count": 37
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..f8e6aea
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,1,0,0.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,666.449,0.000,0.071,0.000,0.009,0.000,30.044,0.000,30.025,0.000,0.002,0.000,0.019,0.000,251.079,0.000,90.503,0.000,605.250,0.000,485.375,0.000,100.769,0.000,100.141,0.000
+5000000,10,1,0,0.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,3981.266,0.000,0.230,0.000,0.011,0.000,30.032,0.000,30.020,0.000,0.000,0.000,0.012,0.000,1227.531,0.000,413.007,0.000,2656.359,0.000,2022.955,0.000,101.707,0.000,92.056,0.000
+10000000,10,1,0,0.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,9329.224,0.000,0.416,0.000,0.011,0.000,30.039,0.000,30.022,0.000,0.004,0.000,0.017,0.000,2532.608,0.000,843.823,0.000,4143.891,0.000,3433.151,0.000,101.127,0.000,83.006,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline_results.md
new file mode 100644
index 0000000..ddc9f0f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781285296228/query_defined_baseline_results.md
@@ -0,0 +1,5 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 666.449 ± 0.000 | 0.071 ± 0.000 | 0.009 ± 0.000 | 0.019 ± 0.000 | 605.250 ± 0.000 | 100.141 ± 0.000 | 0.000 |
+| 5000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 3981.266 ± 0.000 | 0.230 ± 0.000 | 0.011 ± 0.000 | 0.012 ± 0.000 | 2656.359 ± 0.000 | 92.056 ± 0.000 | 0.000 |
+| 10000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 9329.224 ± 0.000 | 0.416 ± 0.000 | 0.011 ± 0.000 | 0.017 ± 0.000 | 4143.891 ± 0.000 | 83.006 ± 0.000 | 0.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.raw.json
new file mode 100644
index 0000000..0cb1611
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.raw.json
@@ -0,0 +1,393 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1M --baseline-entities 10 --verbose",
+    "timestamp_unix_ms": 1781286210279
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": false,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781286210210",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 243.76789299650295,
+        "storage_write_ms": 90.15137899997812,
+        "baseline_eval_ms": 655.657875,
+        "materialization_ms": 0.106458,
+        "static_injection_ms": 0.009958,
+        "historical_query_ms": 655.657875,
+        "baseline_materialization_ms": 0.106458,
+        "static_graph_injection_ms": 0.009958,
+        "live_startup_ms": 0.0015409999999999998,
+        "first_result_latency_ms": 30.103708,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": false,
+        "correctness_diagnostics": {
+          "variant": "baseline",
+          "expected_result_count": 10,
+          "observed_result_count": 10,
+          "expected_emitted_windows": 0,
+          "observed_emitted_windows": 1,
+          "expected_variables": [
+            "sensor",
+            "minuteAvgValue",
+            "dayAvgValue",
+            "difference"
+          ],
+          "observed_variables": [
+            "sensor",
+            "minuteAvgValue",
+            "dayAvgValue",
+            "difference"
+          ],
+          "first_observed_rows": [
+            {
+              "sensor": "http://example.org/sensor0",
+              "minute_avg_value": 20.0,
+              "day_avg_value": 10.0,
+              "difference": 10.0,
+              "received_after_first_event_ms": 30.103708,
+              "timestamp_from": 1090,
+              "timestamp_to": 61090
+            },
+            {
+              "sensor": "http://example.org/sensor1",
+              "minute_avg_value": 30.0,
+              "day_avg_value": 11.0,
+              "difference": 19.0,
+              "received_after_first_event_ms": 30.103749999999998,
+              "timestamp_from": 1090,
+              "timestamp_to": 61090
+            },
+            {
+              "sensor": "http://example.org/sensor2",
+              "minute_avg_value": 40.0,
+              "day_avg_value": 12.0,
+              "difference": 28.0,
+              "received_after_first_event_ms": 30.104333,
+              "timestamp_from": 1090,
+              "timestamp_to": 61090
+            }
+          ],
+          "reason": "missing expected day aggregate for sensor http://example.org/sensor0"
+        },
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.103708,
+          30.103749999999998,
+          30.104333,
+          30.105583000000003,
+          30.103792000000002,
+          30.103833,
+          30.104458,
+          30.104374999999997,
+          30.102166999999998,
+          30.104417
+        ],
+        "completed_window_latencies_ms": [
+          30.102166999999998
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.103708,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.103749999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.104333,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.105583000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.103792000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.103833,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.104458,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.104374999999997,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.102166999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.104417,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 243.76789299650295,
+        "storage_write_ms": 90.15137899997812,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001583,
+        "first_result_latency_ms": 30.034791000000002,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.034791000000002,
+          30.036,
+          30.035958,
+          30.036083,
+          30.036125000000002,
+          30.036625,
+          30.036707999999997,
+          30.036791,
+          30.037541,
+          30.036666
+        ],
+        "completed_window_latencies_ms": [
+          30.034791000000002,
+          30.035958,
+          30.036083,
+          30.036666
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.034791000000002,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.035958,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036083,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036125000000002,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036625,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036707999999997,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036791,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.037541,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.036666,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0,
+      "first_result_overhead_ms": 0.068916999999999,
+      "peak_rss_mb": 611.203125,
+      "mean_rss_mb": 489.8203125,
+      "peak_cpu_percent": 99.6850814819336,
+      "mean_cpu_percent": 99.63555908203125,
+      "sample_count": 2
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..8bfd451
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,1,0,0.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,655.658,0.000,0.106,0.000,0.010,0.000,30.104,0.000,30.035,0.000,0.000,0.000,0.069,0.000,243.768,0.000,90.151,0.000,611.203,0.000,489.820,0.000,99.685,0.000,99.636,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline_results.md
new file mode 100644
index 0000000..8474e0a
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286210210/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 655.658 ± 0.000 | 0.106 ± 0.000 | 0.010 ± 0.000 | 0.069 ± 0.000 | 611.203 ± 0.000 | 99.636 ± 0.000 | 0.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.raw.json
new file mode 100644
index 0000000..c5df471
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.raw.json
@@ -0,0 +1,345 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1M --baseline-entities 10 --verbose",
+    "timestamp_unix_ms": 1781286283238
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781286283169",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 252.3046749963325,
+        "storage_write_ms": 88.2756810000066,
+        "baseline_eval_ms": 652.1368749999999,
+        "materialization_ms": 0.069708,
+        "static_injection_ms": 0.007,
+        "historical_query_ms": 652.1368749999999,
+        "baseline_materialization_ms": 0.069708,
+        "static_graph_injection_ms": 0.007,
+        "live_startup_ms": 0.001667,
+        "first_result_latency_ms": 28.523,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          28.523,
+          28.52475,
+          28.526292,
+          28.527542,
+          28.524959,
+          28.525167,
+          28.526959,
+          28.526584,
+          28.5245,
+          28.526792
+        ],
+        "completed_window_latencies_ms": [
+          28.523
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 28.523,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 28.52475,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 28.526292,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 28.527542,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 28.524959,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 28.525167,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 28.526959,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 28.526584,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 28.5245,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 28.526792,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 252.3046749963325,
+        "storage_write_ms": 88.2756810000066,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001375,
+        "first_result_latency_ms": 29.505416999999998,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          29.505416999999998,
+          29.508416999999998,
+          29.508375,
+          29.5085,
+          29.508625,
+          29.509667,
+          29.509875,
+          29.509792,
+          29.510833,
+          29.509917
+        ],
+        "completed_window_latencies_ms": [
+          29.505416999999998,
+          29.508375,
+          29.5085,
+          29.509792
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.505416999999998,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.508416999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.508375,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.5085,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.508625,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.509667,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.509875,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.509792,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.510833,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 29.509917,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00029200000000000016,
+      "first_result_overhead_ms": 0.0,
+      "peak_rss_mb": 614.78125,
+      "mean_rss_mb": 496.0234375,
+      "peak_cpu_percent": 102.0879135131836,
+      "mean_cpu_percent": 100.5811538696289,
+      "sample_count": 2
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..4f6518d
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,1,0,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,652.137,0.000,0.070,0.000,0.007,0.000,28.523,0.000,29.505,0.000,0.000,0.000,0.000,0.000,252.305,0.000,88.276,0.000,614.781,0.000,496.023,0.000,102.088,0.000,100.581,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline_results.md
new file mode 100644
index 0000000..ecaf41c
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286283169/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 652.137 ± 0.000 | 0.070 ± 0.000 | 0.007 ± 0.000 | 0.000 ± 0.000 | 614.781 ± 0.000 | 100.581 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.raw.json
new file mode 100644
index 0000000..73ee663
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.raw.json
@@ -0,0 +1,977 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1M,5M,10M --baseline-entities 10",
+    "timestamp_unix_ms": 1781286288354
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000,
+    5000000,
+    10000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781286288255",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 547.1259359994538,
+        "storage_write_ms": 203.5926209979438,
+        "baseline_eval_ms": 1232.934792,
+        "materialization_ms": 0.121458,
+        "static_injection_ms": 0.00675,
+        "historical_query_ms": 1232.934792,
+        "baseline_materialization_ms": 0.121458,
+        "static_graph_injection_ms": 0.00675,
+        "live_startup_ms": 0.0012079999999999999,
+        "first_result_latency_ms": 28.167917,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          28.167917,
+          28.170167,
+          28.172084,
+          28.17,
+          28.170292,
+          28.170334,
+          28.17225,
+          28.172042,
+          28.172916999999998,
+          28.172167
+        ],
+        "completed_window_latencies_ms": [
+          28.167917
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 28.167917,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 28.170167,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 28.172084,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 28.17,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 28.170292,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 28.170334,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 28.17225,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 28.172042,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 28.172916999999998,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 28.172167,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 547.1259359994538,
+        "storage_write_ms": 203.5926209979438,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.0029579999999999997,
+        "first_result_latency_ms": 26.376292,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          26.376292,
+          26.379084,
+          26.378917,
+          26.380542,
+          26.379375,
+          26.379125,
+          26.380625000000002,
+          26.380709,
+          26.381709,
+          26.380667
+        ],
+        "completed_window_latencies_ms": [
+          26.376292,
+          26.378917,
+          26.379125,
+          26.380625000000002
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 26.376292,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 26.379084,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 26.378917,
+            "timestamp_from": 1010,
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+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.027041,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026833,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02725,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0002499999999999998,
+      "first_result_overhead_ms": 0.06858400000000131,
+      "peak_rss_mb": 4450.859375,
+      "mean_rss_mb": 3447.089226973684,
+      "peak_cpu_percent": 103.09814453125,
+      "mean_cpu_percent": 79.33423032258686,
+      "sample_count": 38
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..1624098
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,1,0,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,1232.935,0.000,0.121,0.000,0.007,0.000,28.168,0.000,26.376,0.000,0.000,0.000,1.792,0.000,547.126,0.000,203.593,0.000,616.484,0.000,440.797,0.000,87.095,0.000,77.838,0.000
+5000000,10,1,0,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,3515.826,0.000,0.311,0.000,0.008,0.000,29.991,0.000,28.405,0.000,0.001,0.000,1.586,0.000,1365.306,0.000,449.172,0.000,2997.672,0.000,2200.475,0.000,102.835,0.000,98.516,0.000
+10000000,10,1,0,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,9687.754,0.000,0.735,0.000,0.028,0.000,30.093,0.000,30.024,0.000,0.000,0.000,0.069,0.000,2500.463,0.000,829.427,0.000,4450.859,0.000,3447.089,0.000,103.098,0.000,79.334,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline_results.md
new file mode 100644
index 0000000..4e744a1
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286288255/query_defined_baseline_results.md
@@ -0,0 +1,5 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 1232.935 ± 0.000 | 0.121 ± 0.000 | 0.007 ± 0.000 | 1.792 ± 0.000 | 616.484 ± 0.000 | 77.838 ± 0.000 | 1.000 |
+| 5000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 3515.826 ± 0.000 | 0.311 ± 0.000 | 0.008 ± 0.000 | 1.586 ± 0.000 | 2997.672 ± 0.000 | 98.516 ± 0.000 | 1.000 |
+| 10000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 9687.754 ± 0.000 | 0.735 ± 0.000 | 0.028 ± 0.000 | 0.069 ± 0.000 | 4450.859 ± 0.000 | 79.334 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.raw.json
new file mode 100644
index 0000000..7384cea
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.raw.json
@@ -0,0 +1,345 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 0 --runs 1 --historical-events 1M --baseline-entities 10",
+    "timestamp_unix_ms": 1781286974370
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 1,
+  "warmup_runs": 0,
+  "historical_events": [
+    1000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781286974304",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 288.1201000005497,
+        "storage_write_ms": 93.94413200005417,
+        "baseline_eval_ms": 656.4579160000001,
+        "materialization_ms": 0.058542000000000004,
+        "static_injection_ms": 0.010417000000000001,
+        "historical_query_ms": 656.4579160000001,
+        "baseline_materialization_ms": 0.058542000000000004,
+        "static_graph_injection_ms": 0.010417000000000001,
+        "live_startup_ms": 0.001333,
+        "first_result_latency_ms": 30.036458,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.036458,
+          30.036666,
+          30.037916000000003,
+          30.034875,
+          30.036875000000002,
+          30.037041000000002,
+          30.0385,
+          30.038083,
+          30.038833,
+          30.038291
+        ],
+        "completed_window_latencies_ms": [
+          30.034875
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.036458,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.036666,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.037916000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.034875,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.036875000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.037041000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.0385,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.038083,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.038833,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.038291,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 288.1201000005497,
+        "storage_write_ms": 93.94413200005417,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.001041,
+        "first_result_latency_ms": 30.023416,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.023416,
+          30.024541,
+          30.024375,
+          30.025666,
+          30.024915999999997,
+          30.02475,
+          30.026791,
+          30.026291,
+          30.025875,
+          30.026500000000002
+        ],
+        "completed_window_latencies_ms": [
+          30.023416,
+          30.024375,
+          30.02475,
+          30.025875
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023416,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024541,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024375,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025666,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.024915999999997,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02475,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026791,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026291,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.025875,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.026500000000002,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.00029199999999999994,
+      "first_result_overhead_ms": 0.013041999999998666,
+      "peak_rss_mb": 614.65625,
+      "mean_rss_mb": 497.9296875,
+      "peak_cpu_percent": 100.3084487915039,
+      "mean_cpu_percent": 99.98466110229492,
+      "sample_count": 2
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..29e774a
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline.summary.csv
@@ -0,0 +1,2 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,1,0,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,656.458,0.000,0.059,0.000,0.010,0.000,30.036,0.000,30.023,0.000,0.000,0.000,0.013,0.000,288.120,0.000,93.944,0.000,614.656,0.000,497.930,0.000,100.308,0.000,99.985,0.000
diff --git a/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline_results.md
new file mode 100644
index 0000000..1e5519f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781286974304/query_defined_baseline_results.md
@@ -0,0 +1,3 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 656.458 ± 0.000 | 0.059 ± 0.000 | 0.010 ± 0.000 | 0.013 ± 0.000 | 614.656 ± 0.000 | 99.985 ± 0.000 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.raw.json
new file mode 100644
index 0000000..f682398
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.raw.json
@@ -0,0 +1,3812 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 3 --historical-events 1M,5M,10M --baseline-entities 10",
+    "timestamp_unix_ms": 1781287256513
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 3,
+  "warmup_runs": 1,
+  "historical_events": [
+    1000000,
+    5000000,
+    10000000
+  ],
+  "baseline_entities": [
+    10
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781287256463",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 10,
+      "is_warmup": true,
+      "run_index": 0,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
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+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.027958,
+          30.029041,
+          30.028833000000002,
+          30.030082999999998,
+          30.029457999999998,
+          30.02925,
+          30.030250000000002,
+          30.030666,
+          30.030958,
+          30.030458
+        ],
+        "completed_window_latencies_ms": [
+          30.027958,
+          30.028833000000002,
+          30.02925,
+          30.030250000000002
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.027958,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029041,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.028833000000002,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030082999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.029457999999998,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02925,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030250000000002,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030666,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030958,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.030458,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0006249999999999999,
+      "first_result_overhead_ms": 0.0025009999999987542,
+      "peak_rss_mb": 5111.90625,
+      "mean_rss_mb": 4826.259290540541,
+      "peak_cpu_percent": 101.38420867919922,
+      "mean_cpu_percent": 83.53190086983345,
+      "sample_count": 37
+    },
+    {
+      "historical_events": 10000000,
+      "baseline_entities": 10,
+      "is_warmup": false,
+      "run_index": 2,
+      "observed_baseline_rows": 10,
+      "observed_live_only_rows": 10,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 2,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 2500.637916232409,
+        "storage_write_ms": 891.7252821093962,
+        "baseline_eval_ms": 8772.347625,
+        "materialization_ms": 0.181375,
+        "static_injection_ms": 0.019541000000000003,
+        "historical_query_ms": 8772.347625,
+        "baseline_materialization_ms": 0.181375,
+        "static_graph_injection_ms": 0.019541000000000003,
+        "live_startup_ms": 0.0018750000000000001,
+        "first_result_latency_ms": 30.038959000000002,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": 10,
+        "baseline_binding_count": 10,
+        "window_result_latencies_ms": [
+          30.038959000000002,
+          30.039334,
+          30.040459,
+          30.041334,
+          30.039541999999997,
+          30.03975,
+          30.041042,
+          30.040667,
+          30.03775,
+          30.040875000000003
+        ],
+        "completed_window_latencies_ms": [
+          30.03775
+        ],
+        "completed_window_result_counts": [
+          10
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": 10.0,
+            "difference": 10.0,
+            "received_after_first_event_ms": 30.038959000000002,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": 11.0,
+            "difference": 19.0,
+            "received_after_first_event_ms": 30.039334,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": 12.0,
+            "difference": 28.0,
+            "received_after_first_event_ms": 30.040459,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": 13.0,
+            "difference": 37.0,
+            "received_after_first_event_ms": 30.041334,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor4",
+            "minute_avg_value": 60.0,
+            "day_avg_value": 14.0,
+            "difference": 46.0,
+            "received_after_first_event_ms": 30.039541999999997,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor5",
+            "minute_avg_value": 70.0,
+            "day_avg_value": 15.0,
+            "difference": 55.0,
+            "received_after_first_event_ms": 30.03975,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor6",
+            "minute_avg_value": 80.0,
+            "day_avg_value": 16.0,
+            "difference": 64.0,
+            "received_after_first_event_ms": 30.041042,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor7",
+            "minute_avg_value": 90.0,
+            "day_avg_value": 17.0,
+            "difference": 73.0,
+            "received_after_first_event_ms": 30.040667,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
+            "day_avg_value": 18.0,
+            "difference": 82.0,
+            "received_after_first_event_ms": 30.03775,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          },
+          {
+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
+            "day_avg_value": 19.0,
+            "difference": 91.0,
+            "received_after_first_event_ms": 30.040875000000003,
+            "timestamp_from": 1090,
+            "timestamp_to": 61090
+          }
+        ]
+      },
+      "live_only": {
+        "variant": "live_only",
+        "run_index": 2,
+        "historical_events": 10000000,
+        "baseline_entities": 10,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 10,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 4,
+        "window_semantics_note": null,
+        "historical_generation_ms": 2500.637916232409,
+        "storage_write_ms": 891.7252821093962,
+        "baseline_eval_ms": null,
+        "materialization_ms": null,
+        "static_injection_ms": null,
+        "historical_query_ms": null,
+        "baseline_materialization_ms": null,
+        "static_graph_injection_ms": null,
+        "live_startup_ms": 0.000959,
+        "first_result_latency_ms": 30.021040999999997,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
+        "sample_count": 0,
+        "result_count": 10,
+        "correctness_ok": true,
+        "correctness_diagnostics": null,
+        "materialized_quad_count": null,
+        "baseline_binding_count": null,
+        "window_result_latencies_ms": [
+          30.021040999999997,
+          30.022040999999998,
+          30.021875,
+          30.02225,
+          30.022457999999997,
+          30.023041,
+          30.02325,
+          30.023625000000003,
+          30.023958,
+          30.023457999999998
+        ],
+        "completed_window_latencies_ms": [
+          30.021040999999997,
+          30.021875,
+          30.02225,
+          30.02325
+        ],
+        "completed_window_result_counts": [
+          1,
+          2,
+          3,
+          4
+        ],
+        "observed_rows": [
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021040999999997,
+            "timestamp_from": 1000,
+            "timestamp_to": 1060
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.022040999999998,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.021875,
+            "timestamp_from": 1010,
+            "timestamp_to": 1070
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02225,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.022457999999997,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023041,
+            "timestamp_from": 1020,
+            "timestamp_to": 1080
+          },
+          {
+            "sensor": "http://example.org/sensor0",
+            "minute_avg_value": 20.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.02325,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023625000000003,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor2",
+            "minute_avg_value": 40.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023958,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          },
+          {
+            "sensor": "http://example.org/sensor3",
+            "minute_avg_value": 50.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.023457999999998,
+            "timestamp_from": 1030,
+            "timestamp_to": 1090
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.0009160000000000001,
+      "first_result_overhead_ms": 0.017918000000005208,
+      "peak_rss_mb": 5080.578125,
+      "mean_rss_mb": 4843.84375,
+      "peak_cpu_percent": 101.8422622680664,
+      "mean_cpu_percent": 85.9356475830078,
+      "sample_count": 35
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..36fc00f
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline.summary.csv
@@ -0,0 +1,4 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,10,3,1,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,681.214,71.693,0.042,0.006,0.011,0.001,28.503,2.642,28.567,2.258,0.000,0.000,1.356,2.349,259.438,0.000,92.315,0.000,636.047,15.612,598.188,49.392,100.486,0.833,98.032,3.404
+5000000,10,3,1,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,3224.019,254.798,0.156,0.005,0.013,0.001,30.029,0.004,29.796,0.396,0.000,0.000,0.233,0.392,1219.236,0.000,406.236,0.000,3162.609,67.090,2974.306,307.746,102.664,0.638,99.459,1.481
+10000000,10,3,1,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,8638.362,640.063,0.305,0.108,0.019,0.001,30.037,0.005,29.598,0.739,0.001,0.000,0.439,0.743,2500.638,0.000,891.725,0.000,4998.073,170.754,4620.369,371.945,101.979,0.674,86.780,3.742
diff --git a/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline_results.md
new file mode 100644
index 0000000..e4a32c6
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287256463/query_defined_baseline_results.md
@@ -0,0 +1,5 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 681.214 ± 71.693 | 0.042 ± 0.006 | 0.011 ± 0.001 | 1.356 ± 2.349 | 636.047 ± 15.612 | 98.032 ± 3.404 | 1.000 |
+| 5000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 3224.019 ± 254.798 | 0.156 ± 0.005 | 0.013 ± 0.001 | 0.233 ± 0.392 | 3162.609 ± 67.090 | 99.459 ± 1.481 | 1.000 |
+| 10000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 8638.362 ± 640.063 | 0.305 ± 0.108 | 0.019 ± 0.001 | 0.439 ± 0.743 | 4998.073 ± 170.754 | 86.780 ± 3.742 | 1.000 |
diff --git a/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.raw.json b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.raw.json
new file mode 100644
index 0000000..20bc0a6
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.raw.json
@@ -0,0 +1,906102 @@
+{
+  "metadata": {
+    "git_commit_sha": "b9da83e012fb88997265b533077f218fa5453236",
+    "branch": "benchmark-paper-hybrid-scaling",
+    "rustc_version": "rustc 1.90.0 (1159e78c4 2025-09-14)",
+    "os": "macos 25.5.0",
+    "cpu_model": "Apple M4",
+    "ram_bytes": 17179869184,
+    "benchmark_command": "target/release/paper_query_defined_baseline --warmup-runs 1 --runs 3 --historical-events 1M --baseline-entities 1,10,100,1000,10000",
+    "timestamp_unix_ms": 1781287455940
+  },
+  "profile": "smoke",
+  "live_replay_mode": "accelerated",
+  "live_rate_hz": 4.0,
+  "live_duration_seconds": null,
+  "live_window_size_seconds": null,
+  "live_window_slide_seconds": null,
+  "runs": 3,
+  "warmup_runs": 1,
+  "historical_events": [
+    1000000
+  ],
+  "baseline_entities": [
+    1,
+    10,
+    100,
+    1000,
+    10000
+  ],
+  "correctness_passed": true,
+  "output_dir": "logs/benchmark/query_defined_baseline/1781287455874",
+  "comparisons": [
+    {
+      "historical_events": 1000000,
+      "baseline_entities": 1,
+      "is_warmup": true,
+      "run_index": 0,
+      "observed_baseline_rows": 1,
+      "observed_live_only_rows": 1,
+      "baseline": {
+        "variant": "baseline",
+        "run_index": 0,
+        "historical_events": 1000000,
+        "baseline_entities": 1,
+        "live_replay_mode": "accelerated",
+        "live_rate_hz": 4.0,
+        "live_duration_seconds": null,
+        "live_window_size_seconds": null,
+        "live_window_slide_seconds": null,
+        "live_event_count": 1,
+        "expected_emitted_windows": 0,
+        "expected_full_windows": 0,
+        "warmup_window_count": null,
+        "observed_emitted_windows": 1,
+        "window_semantics_note": null,
+        "historical_generation_ms": 274.71810899869877,
+        "storage_write_ms": 95.02534199973782,
+        "baseline_eval_ms": 650.271167,
+        "materialization_ms": 0.042916,
+        "static_injection_ms": 0.0022919999999999998,
+        "historical_query_ms": 650.271167,
+        "baseline_materialization_ms": 0.042916,
+        "static_graph_injection_ms": 0.0022919999999999998,
+        "live_startup_ms": 0.00175,
+        "first_result_latency_ms": 30.033875000000002,
+        "peak_rss_mb": null,
+        "mean_rss_mb": null,
+        "peak_cpu_percent": null,
+        "mean_cpu_percent": null,
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+            "minute_avg_value": 850.0,
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+            "sensor": "http://example.org/sensor84",
+            "minute_avg_value": 860.0,
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+            "minute_avg_value": 870.0,
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+            "sensor": "http://example.org/sensor86",
+            "minute_avg_value": 880.0,
+            "day_avg_value": 96.0,
+            "difference": 784.0,
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+            "minute_avg_value": 750.0,
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+            "received_after_first_event_ms": 26.040208,
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+            "minute_avg_value": 770.0,
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+            "received_after_first_event_ms": 26.0415,
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+            "minute_avg_value": 780.0,
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+            "received_after_first_event_ms": 26.025291,
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+            "sensor": "http://example.org/sensor54",
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+            "sensor": "http://example.org/sensor55",
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+          {
+            "sensor": "http://example.org/sensor57",
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+          {
+            "sensor": "http://example.org/sensor58",
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+            "timestamp_from": 1990,
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+          {
+            "sensor": "http://example.org/sensor59",
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+            "sensor": "http://example.org/sensor23",
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+            "sensor": "http://example.org/sensor26",
+            "minute_avg_value": 280.0,
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+          {
+            "sensor": "http://example.org/sensor27",
+            "minute_avg_value": 290.0,
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+            "minute_avg_value": 1010.0,
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+            "sensor": "http://example.org/sensor0",
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+            "timestamp_to": 62990
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+            "sensor": "http://example.org/sensor1",
+            "minute_avg_value": 30.0,
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+            "sensor": "http://example.org/sensor10",
+            "minute_avg_value": 120.0,
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+            "received_after_first_event_ms": 30.63325,
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+            "minute_avg_value": 1020.0,
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+            "minute_avg_value": 1030.0,
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+            "sensor": "http://example.org/sensor25",
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+            "sensor": "http://example.org/sensor26",
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+            "timestamp_to": 2070
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+            "timestamp_to": 2070
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+          {
+            "sensor": "http://example.org/sensor100",
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+            "received_after_first_event_ms": 30.628,
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+            "timestamp_to": 2080
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+          {
+            "sensor": "http://example.org/sensor101",
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+            "timestamp_from": 2020,
+            "timestamp_to": 2080
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+          {
+            "sensor": "http://example.org/sensor102",
+            "minute_avg_value": 1040.0,
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+            "received_after_first_event_ms": 30.628042,
+            "timestamp_from": 2020,
+            "timestamp_to": 2080
+          },
+          {
+            "sensor": "http://example.org/sensor97",
+            "minute_avg_value": 990.0,
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+            "received_after_first_event_ms": 30.628167,
+            "timestamp_from": 2020,
+            "timestamp_to": 2080
+          },
+          {
+            "sensor": "http://example.org/sensor98",
+            "minute_avg_value": 1000.0,
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+            "received_after_first_event_ms": 30.628125,
+            "timestamp_from": 2020,
+            "timestamp_to": 2080
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+          {
+            "sensor": "http://example.org/sensor99",
+            "minute_avg_value": 1010.0,
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+            "minute_avg_value": 1010.0,
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+            "sensor": "http://example.org/sensor24",
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+            "timestamp_to": 2040
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+          {
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+            "timestamp_to": 2050
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+          {
+            "sensor": "http://example.org/sensor95",
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+            "timestamp_to": 2050
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+            "sensor": "http://example.org/sensor96",
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+            "timestamp_to": 2050
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+            "timestamp_to": 2050
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+            "sensor": "http://example.org/sensor98",
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+            "timestamp_from": 1990,
+            "timestamp_to": 2050
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+          {
+            "sensor": "http://example.org/sensor99",
+            "minute_avg_value": 1010.0,
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+            "timestamp_from": 1990,
+            "timestamp_to": 2050
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+          {
+            "sensor": "http://example.org/sensor100",
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+            "received_after_first_event_ms": 30.868083000000002,
+            "timestamp_from": 2000,
+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor95",
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+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor96",
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+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor97",
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+            "received_after_first_event_ms": 30.868333,
+            "timestamp_from": 2000,
+            "timestamp_to": 2060
+          },
+          {
+            "sensor": "http://example.org/sensor98",
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+            "received_after_first_event_ms": 30.86825,
+            "timestamp_from": 2000,
+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor99",
+            "minute_avg_value": 1010.0,
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+            "received_after_first_event_ms": 30.868125,
+            "timestamp_from": 2000,
+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor100",
+            "minute_avg_value": 1020.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.868416999999997,
+            "timestamp_from": 2010,
+            "timestamp_to": 2070
+          },
+          {
+            "sensor": "http://example.org/sensor101",
+            "minute_avg_value": 1030.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.868583,
+            "timestamp_from": 2010,
+            "timestamp_to": 2070
+          },
+          {
+            "sensor": "http://example.org/sensor96",
+            "minute_avg_value": 980.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 30.868625,
+            "timestamp_from": 2010,
+            "timestamp_to": 2070
+          },
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+            "minute_avg_value": 900.0,
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+            "difference": 802.0,
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+            "sensor": "http://example.org/sensor9",
+            "minute_avg_value": 110.0,
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+            "difference": 91.0,
+            "received_after_first_event_ms": 30.25775,
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+            "minute_avg_value": 920.0,
+            "day_avg_value": 100.0,
+            "difference": 820.0,
+            "received_after_first_event_ms": 30.257125,
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+            "sensor": "http://example.org/sensor91",
+            "minute_avg_value": 930.0,
+            "day_avg_value": 101.0,
+            "difference": 829.0,
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+            "timestamp_from": 1990,
+            "timestamp_to": 61990
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+            "sensor": "http://example.org/sensor92",
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+            "sensor": "http://example.org/sensor23",
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+            "timestamp_to": 2050
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+            "sensor": "http://example.org/sensor98",
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+            "timestamp_to": 2050
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+          {
+            "sensor": "http://example.org/sensor99",
+            "minute_avg_value": 1010.0,
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+            "received_after_first_event_ms": 30.644125000000003,
+            "timestamp_from": 1990,
+            "timestamp_to": 2050
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+          {
+            "sensor": "http://example.org/sensor100",
+            "minute_avg_value": 1020.0,
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+            "received_after_first_event_ms": 30.64475,
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+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor95",
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+            "timestamp_to": 2060
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+            "sensor": "http://example.org/sensor96",
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+            "timestamp_from": 2000,
+            "timestamp_to": 2060
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+          {
+            "sensor": "http://example.org/sensor97",
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+            "minute_avg_value": 780.0,
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+            "received_after_first_event_ms": 36.369458,
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+            "minute_avg_value": 790.0,
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+            "received_after_first_event_ms": 36.366208,
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+            "sensor": "http://example.org/sensor78",
+            "minute_avg_value": 800.0,
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+            "difference": 712.0,
+            "received_after_first_event_ms": 36.369125000000004,
+            "timestamp_from": 1990,
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+            "sensor": "http://example.org/sensor79",
+            "minute_avg_value": 810.0,
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+            "sensor": "http://example.org/sensor8",
+            "minute_avg_value": 100.0,
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+            "difference": 82.0,
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+        "baseline_entities": 10000,
+        "live_replay_mode": "accelerated",
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+        "live_duration_seconds": null,
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+        "live_event_count": 10000,
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+        "warmup_window_count": null,
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+            "sensor": "http://example.org/sensor91",
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+            "received_after_first_event_ms": 36.586292,
+            "timestamp_from": 1960,
+            "timestamp_to": 2020
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+            "sensor": "http://example.org/sensor93",
+            "minute_avg_value": 950.0,
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+            "timestamp_to": 2020
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+            "timestamp_to": 2040
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+            "timestamp_to": 2040
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+            "timestamp_to": 2050
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+            "timestamp_to": 2050
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+            "timestamp_to": 2050
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+            "timestamp_to": 2050
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+            "timestamp_to": 2050
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+            "sensor": "http://example.org/sensor106",
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+          {
+            "sensor": "http://example.org/sensor107",
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+            "sensor": "http://example.org/sensor103",
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+            "timestamp_from": 2080,
+            "timestamp_to": 2140
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+            "sensor": "http://example.org/sensor104",
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+            "sensor": "http://example.org/sensor27",
+            "minute_avg_value": 290.0,
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+            "timestamp_to": 2050
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+            "sensor": "http://example.org/sensor99",
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+            "timestamp_from": 2020,
+            "timestamp_to": 2080
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+          {
+            "sensor": "http://example.org/sensor100",
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+            "received_after_first_event_ms": 40.67875,
+            "timestamp_from": 2030,
+            "timestamp_to": 2090
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+          {
+            "sensor": "http://example.org/sensor101",
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+            "timestamp_from": 2030,
+            "timestamp_to": 2090
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+          {
+            "sensor": "http://example.org/sensor102",
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+            "timestamp_to": 2090
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+          {
+            "sensor": "http://example.org/sensor103",
+            "minute_avg_value": 1050.0,
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+            "received_after_first_event_ms": 40.679,
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+            "timestamp_to": 2090
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+          {
+            "sensor": "http://example.org/sensor98",
+            "minute_avg_value": 1000.0,
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+            "sensor": "http://example.org/sensor27",
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+            "timestamp_from": 1280,
+            "timestamp_to": 1340
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+            "sensor": "http://example.org/sensor25",
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+            "sensor": "http://example.org/sensor26",
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+            "received_after_first_event_ms": 37.196,
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+            "timestamp_to": 2100
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+            "sensor": "http://example.org/sensor101",
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+            "minute_avg_value": 16550.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40899999999999,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1654",
+            "minute_avg_value": 16560.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409124999999996,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1655",
+            "minute_avg_value": 16570.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.408959,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1656",
+            "minute_avg_value": 16580.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40908400000001,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1657",
+            "minute_avg_value": 16590.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409167000000004,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409042,
+            "timestamp_from": 17580,
+            "timestamp_to": 17640
+          },
+          {
+            "sensor": "http://example.org/sensor1654",
+            "minute_avg_value": 16560.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40929200000001,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1655",
+            "minute_avg_value": 16570.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409209,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1656",
+            "minute_avg_value": 16580.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409375000000004,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1657",
+            "minute_avg_value": 16590.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409459,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409334,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409417,
+            "timestamp_from": 17590,
+            "timestamp_to": 17650
+          },
+          {
+            "sensor": "http://example.org/sensor1655",
+            "minute_avg_value": 16570.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409499999999994,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1656",
+            "minute_avg_value": 16580.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409625,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1657",
+            "minute_avg_value": 16590.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40975,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409542,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409667000000006,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409584,
+            "timestamp_from": 17600,
+            "timestamp_to": 17660
+          },
+          {
+            "sensor": "http://example.org/sensor1656",
+            "minute_avg_value": 16580.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40991699999999,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1657",
+            "minute_avg_value": 16590.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409834,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409959,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.40987500000001,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.409792,
+            "timestamp_from": 17610,
+            "timestamp_to": 17670
+          },
+          {
+            "sensor": "http://example.org/sensor1657",
+            "minute_avg_value": 16590.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410208999999995,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410084000000005,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410250000000005,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410125,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410042,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410167,
+            "timestamp_from": 17620,
+            "timestamp_to": 17680
+          },
+          {
+            "sensor": "http://example.org/sensor1658",
+            "minute_avg_value": 16600.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410375,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410459,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410416999999995,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41029199999999,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410542,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41049999999999,
+            "timestamp_from": 17630,
+            "timestamp_to": 17690
+          },
+          {
+            "sensor": "http://example.org/sensor1659",
+            "minute_avg_value": 16610.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410709,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410624999999996,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41058400000001,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410667000000004,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41075,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1664",
+            "minute_avg_value": 16660.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410791999999994,
+            "timestamp_from": 17640,
+            "timestamp_to": 17700
+          },
+          {
+            "sensor": "http://example.org/sensor1660",
+            "minute_avg_value": 16620.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410875000000004,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410834,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410959000000005,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411042,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1664",
+            "minute_avg_value": 16660.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.410917,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1665",
+            "minute_avg_value": 16670.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41108400000001,
+            "timestamp_from": 17650,
+            "timestamp_to": 17710
+          },
+          {
+            "sensor": "http://example.org/sensor1661",
+            "minute_avg_value": 16630.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411125,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41125,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411334,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1664",
+            "minute_avg_value": 16660.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411167000000006,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1665",
+            "minute_avg_value": 16670.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411291999999996,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1666",
+            "minute_avg_value": 16680.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411209,
+            "timestamp_from": 17660,
+            "timestamp_to": 17720
+          },
+          {
+            "sensor": "http://example.org/sensor1662",
+            "minute_avg_value": 16640.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411542000000004,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41137500000001,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1664",
+            "minute_avg_value": 16660.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411459,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1665",
+            "minute_avg_value": 16670.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41158399999999,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1666",
+            "minute_avg_value": 16680.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.4115,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1667",
+            "minute_avg_value": 16690.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411625,
+            "timestamp_from": 17670,
+            "timestamp_to": 17730
+          },
+          {
+            "sensor": "http://example.org/sensor1663",
+            "minute_avg_value": 16650.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411708999999995,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1664",
+            "minute_avg_value": 16660.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41166700000001,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1665",
+            "minute_avg_value": 16670.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411834,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1666",
+            "minute_avg_value": 16680.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41179199999999,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1667",
+            "minute_avg_value": 16690.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.41187500000001,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1668",
+            "minute_avg_value": 16700.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411750000000005,
+            "timestamp_from": 17680,
+            "timestamp_to": 17740
+          },
+          {
+            "sensor": "http://example.org/sensor1667",
+            "minute_avg_value": 16690.0,
+            "day_avg_value": null,
+            "difference": null,
+            "received_after_first_event_ms": 63.411916999999995,
+            "timestamp_from": 17690,
+            "timestamp_to": 17750
+          }
+        ]
+      },
+      "live_startup_overhead_ms": 0.030624999999999996,
+      "first_result_overhead_ms": 0.001708000000000709,
+      "peak_rss_mb": 2047.484375,
+      "mean_rss_mb": 1997.26953125,
+      "peak_cpu_percent": 423.1134033203125,
+      "mean_cpu_percent": 331.10265350341797,
+      "sample_count": 4
+    }
+  ]
+}
\ No newline at end of file
diff --git a/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.summary.csv b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.summary.csv
new file mode 100644
index 0000000..cd3f69b
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline.summary.csv
@@ -0,0 +1,6 @@
+historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std
+1000000,1,3,1,1.000,0.000,0.000,,1.000,0.000,1.000,0.000,1.000,0.000,1.000,1.000,1.000,1.000,658.163,41.589,0.036,0.005,0.002,0.000,28.891,1.967,30.016,0.004,0.001,0.000,0.008,0.008,274.718,0.000,95.025,0.000,631.688,19.778,588.086,56.250,100.364,0.608,99.170,0.863
+1000000,10,3,1,1.000,0.000,0.000,,1.000,0.000,10.000,0.000,10.000,0.000,10.000,10.000,10.000,10.000,617.124,9.895,0.034,0.007,0.008,0.000,30.031,0.002,30.022,0.001,0.002,0.002,0.009,0.002,257.924,0.000,87.043,0.000,747.359,23.422,747.260,23.414,100.805,1.397,99.407,0.707
+1000000,100,3,1,1.000,0.000,0.000,,1.000,0.000,100.000,0.000,100.000,0.000,100.000,100.000,100.000,100.000,640.111,7.360,0.088,0.011,0.065,0.010,28.759,2.350,29.950,0.239,0.000,0.000,0.018,0.020,267.293,0.000,90.779,0.000,874.052,25.968,873.414,26.443,100.712,1.208,99.685,0.463
+1000000,1000,3,1,1.000,0.000,0.000,,4.000,0.000,1000.000,0.000,1000.000,0.000,1000.000,1000.000,1000.000,1000.000,667.497,24.454,0.414,0.013,0.559,0.025,30.502,0.212,30.669,0.137,0.000,0.000,0.007,0.012,251.059,0.000,84.579,0.000,1104.302,80.200,1101.482,75.862,101.069,1.345,99.539,0.549
+1000000,10000,3,1,1.000,0.000,0.000,,14.000,0.000,10000.000,0.000,10000.000,0.000,10000.000,10000.000,10000.000,10000.000,798.222,40.725,5.116,0.272,6.794,0.366,36.503,0.561,38.095,2.199,0.013,0.015,0.001,0.001,262.558,0.000,92.097,0.000,1870.823,180.357,1807.615,196.203,353.562,62.774,290.690,53.121
diff --git a/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline_results.md b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline_results.md
new file mode 100644
index 0000000..5aca7ca
--- /dev/null
+++ b/logs/benchmark/query_defined_baseline/1781287455874/query_defined_baseline_results.md
@@ -0,0 +1,7 @@
+| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| 1000000 | 1 | 0.000 | 0.000 |  | 1.000 | 1.000 | 1.000 | 1 | 658.163 ± 41.589 | 0.036 ± 0.005 | 0.002 ± 0.000 | 0.008 ± 0.008 | 631.688 ± 19.778 | 99.170 ± 0.863 | 1.000 |
+| 1000000 | 10 | 0.000 | 0.000 |  | 1.000 | 10.000 | 10.000 | 10 | 617.124 ± 9.895 | 0.034 ± 0.007 | 0.008 ± 0.000 | 0.009 ± 0.002 | 747.359 ± 23.422 | 99.407 ± 0.707 | 1.000 |
+| 1000000 | 100 | 0.000 | 0.000 |  | 1.000 | 100.000 | 100.000 | 100 | 640.111 ± 7.360 | 0.088 ± 0.011 | 0.065 ± 0.010 | 0.018 ± 0.020 | 874.052 ± 25.968 | 99.685 ± 0.463 | 1.000 |
+| 1000000 | 1000 | 0.000 | 0.000 |  | 4.000 | 1000.000 | 1000.000 | 1000 | 667.497 ± 24.454 | 0.414 ± 0.013 | 0.559 ± 0.025 | 0.007 ± 0.012 | 1104.302 ± 80.200 | 99.539 ± 0.549 | 1.000 |
+| 1000000 | 10000 | 0.000 | 0.000 |  | 14.000 | 10000.000 | 10000.000 | 10000 | 798.222 ± 40.725 | 5.116 ± 0.272 | 6.794 ± 0.366 | 0.001 ± 0.001 | 1870.823 ± 180.357 | 290.690 ± 53.121 | 1.000 |
diff --git a/src/api/janus_api.rs b/src/api/janus_api.rs
index 86ae114..5b98330 100644
--- a/src/api/janus_api.rs
+++ b/src/api/janus_api.rs
@@ -1,7 +1,9 @@
 use crate::{
     core::RDFEvent,
     execution::{HistoricalExecutor, ResultConverter},
-    parsing::janusql_parser::{JanusQLParser, WindowType},
+    parsing::janusql_parser::{
+        BaselineGraphTemplate, GraphTermTemplate, JanusQLParser, TripleTemplate, WindowType,
+    },
     querying::oxigraph_adapter::OxigraphAdapter,
     registry::query_registry::{BaselineBootstrapMode, QueryId, QueryMetadata, QueryRegistry},
     storage::segmented_storage::StreamingSegmentedStorage,
@@ -10,9 +12,10 @@ use crate::{
         mqtt_subscriber::{MqttSubscriber, MqttSubscriberConfig},
     },
 };
+use oxigraph::model::{BlankNode, GraphName, Literal, NamedNode, NamedOrBlankNode, Quad, Term};
 use std::{
     cmp::Ordering,
-    collections::HashMap,
+    collections::{HashMap, HashSet},
     sync::{
         mpsc::{self, Receiver, Sender},
         Arc, Mutex, RwLock,
@@ -91,6 +94,10 @@ impl QueryHandle {
 struct RunningQuery {
     metadata: QueryMetadata,
     status: Arc<RwLock<ExecutionStatus>>,
+    // Query-defined baselines are evaluated at startup and stored here for
+    // inspection/debugging after they have also been materialized into the
+    // live engine static store.
+    query_defined_baselines: Arc<RwLock<HashMap<String, Vec<HashMap<String, String>>>>>,
     // Primary sender used to send the results to the main subscriber
     primary_sender: Sender<QueryResult>,
     // Additional senders for other subscribers (if any)
@@ -222,29 +229,28 @@ impl JanusApi {
             .unwrap_or(metadata.baseline_mode);
         let effective_baseline_window =
             parsed.baseline.as_ref().map(|baseline| baseline.window_name.clone());
+        validate_query_defined_baseline_access(parsed)?;
+        let requires_async_baseline_warmup = !parsed.live_windows.is_empty()
+            && !parsed.historical_windows.is_empty()
+            && (parsed.baseline.is_some() || !parsed.sparql_queries.is_empty());
         let mut historical_handles = Vec::new();
         let mut shutdown_senders = Vec::new();
-        let initial_status =
-            if !parsed.live_windows.is_empty() && !parsed.historical_windows.is_empty() {
-                ExecutionStatus::WarmingBaseline
-            } else {
-                ExecutionStatus::Running
-            };
+        let initial_status = if requires_async_baseline_warmup {
+            ExecutionStatus::WarmingBaseline
+        } else {
+            ExecutionStatus::Running
+        };
         let status = Arc::new(RwLock::new(initial_status.clone()));
 
         // 4. Spawn historical worker threads (one per historical window)
         for (i, window) in parsed.historical_windows.iter().enumerate() {
             // Get corresponding SPARQL query
-            let sparql_query = parsed
-                .sparql_queries
-                .get(i)
-                .ok_or_else(|| {
-                    JanusApiError::ExecutionError(format!(
-                        "Missing SPARQL query for historical window {}",
-                        i
-                    ))
-                })?
-                .clone();
+            let Some(sparql_query) = parsed.sparql_queries.get(i).cloned() else {
+                // Query-defined baselines may reference historical windows that do not appear
+                // in the registered query WHERE clause, so there is no standalone historical
+                // worker query to run for them.
+                continue;
+            };
 
             let tx = result_tx.clone();
             let storage = Arc::clone(&self.storage);
@@ -310,6 +316,7 @@ impl JanusApi {
         let mut mqtt_subscribers = Vec::new();
         let mut mqtt_subscriber_handles = Vec::new();
         let mut baseline_handle = None;
+        let query_defined_baselines = Arc::new(RwLock::new(HashMap::new()));
 
         let live_handle = if !parsed.live_windows.is_empty() && !parsed.rspql_query.is_empty() {
             let tx = result_tx.clone();
@@ -333,6 +340,18 @@ impl JanusApi {
             // Register all live streams
             {
                 let mut processor = live_processor.lock().unwrap();
+                if !parsed.ast.baseline_uses.is_empty() {
+                    let (_query_defined_baselines, baseline_quads) =
+                        evaluate_and_materialize_query_defined_baselines(
+                            &self.storage,
+                            parsed,
+                            &mpsc::channel::<()>().1,
+                        )?;
+                    if let Ok(mut stored) = query_defined_baselines.write() {
+                        *stored = _query_defined_baselines;
+                    }
+                    materialize_static_quads(&mut processor, &baseline_quads)?;
+                }
                 for window in &live_windows {
                     if let Err(e) = processor.register_stream(&window.stream_name) {
                         eprintln!("Failed to register stream '{}': {}", window.stream_name, e);
@@ -349,13 +368,14 @@ impl JanusApi {
                 }
             }
 
-            if !parsed.historical_windows.is_empty() {
+            if requires_async_baseline_warmup {
                 let storage = Arc::clone(&self.storage);
                 let parsed_clone = parsed.clone();
                 let processor_for_baseline = Arc::clone(&live_processor);
                 let status_for_baseline = Arc::clone(&status);
                 let registry_for_baseline = Arc::clone(&self.registry);
                 let query_id_for_baseline = query_id.clone();
+                let query_defined_baselines_for_thread = Arc::clone(&query_defined_baselines);
                 let baseline_mode = effective_baseline_mode;
                 let baseline_window = effective_baseline_window.clone();
                 let (baseline_shutdown_tx, baseline_shutdown_rx) = mpsc::channel::<()>();
@@ -495,6 +515,7 @@ impl JanusApi {
         let running = RunningQuery {
             metadata,
             status,
+            query_defined_baselines,
             primary_sender: result_tx,
             subscribers: vec![],
             historical_handles,
@@ -587,6 +608,15 @@ impl JanusApi {
             .get(query_id)
             .and_then(|running| running.status.read().ok().map(|s| s.clone()))
     }
+
+    pub fn get_query_defined_baseline_bindings(
+        &self,
+        query_id: &QueryId,
+    ) -> Option<HashMap<String, Vec<HashMap<String, String>>>> {
+        let running_map = self.running.lock().unwrap();
+        let running = running_map.get(query_id)?;
+        running.query_defined_baselines.read().ok().map(|bindings| bindings.clone())
+    }
 }
 
 fn collect_query_baseline_statements(
@@ -611,12 +641,11 @@ fn collect_query_baseline_statements(
             continue;
         }
 
-        let sparql_query = parsed.sparql_queries.get(index).ok_or_else(|| {
-            JanusApiError::ExecutionError(format!(
-                "Missing SPARQL query for historical window {}",
-                index
-            ))
-        })?;
+        let Some(sparql_query) = parsed.sparql_queries.get(index) else {
+            // Query-defined baselines may be the only consumer of a historical window.
+            // In that case there is no main historical SPARQL query to materialize here.
+            continue;
+        };
 
         match window.window_type {
             WindowType::HistoricalFixed => {
@@ -639,6 +668,79 @@ fn collect_query_baseline_statements(
     Ok(statements)
 }
 
+fn collect_query_defined_baseline_bindings(
+    storage: &Arc<StreamingSegmentedStorage>,
+    parsed: &crate::parsing::janusql_parser::ParsedJanusQuery,
+    shutdown_rx: &Receiver<()>,
+) -> Result<HashMap<String, Vec<HashMap<String, String>>>, JanusApiError> {
+    let executor = HistoricalExecutor::new(Arc::clone(storage), OxigraphAdapter::new());
+    let mut baseline_results = HashMap::new();
+
+    for generated in &parsed.generated_baseline_queries {
+        if shutdown_rx.try_recv().is_ok() {
+            return Ok(HashMap::new());
+        }
+
+        let source_window = parsed
+            .historical_windows
+            .iter()
+            .find(|window| window.window_name == generated.source_window)
+            .ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "Missing historical source window '{}' for generated baseline '{}'",
+                    generated.source_window, generated.name
+                ))
+            })?;
+
+        let bindings = execute_generated_baseline_query(
+            &executor,
+            source_window,
+            &generated.sparql_query,
+            shutdown_rx,
+        )?;
+        baseline_results.insert(generated.name.clone(), bindings);
+    }
+
+    Ok(baseline_results)
+}
+
+fn evaluate_and_materialize_query_defined_baselines(
+    storage: &Arc<StreamingSegmentedStorage>,
+    parsed: &crate::parsing::janusql_parser::ParsedJanusQuery,
+    shutdown_rx: &Receiver<()>,
+) -> Result<(HashMap<String, Vec<HashMap<String, String>>>, Vec<Quad>), JanusApiError> {
+    let bindings_by_name = collect_query_defined_baseline_bindings(storage, parsed, shutdown_rx)?;
+    let quads = materialize_query_defined_baseline_quads(parsed, &bindings_by_name)?;
+    Ok((bindings_by_name, quads))
+}
+
+fn execute_generated_baseline_query(
+    executor: &HistoricalExecutor,
+    window: &crate::parsing::janusql_parser::WindowDefinition,
+    sparql_query: &str,
+    shutdown_rx: &Receiver<()>,
+) -> Result<Vec<HashMap<String, String>>, JanusApiError> {
+    match window.window_type {
+        WindowType::HistoricalFixed => executor.execute_fixed_window(window, sparql_query),
+        WindowType::HistoricalSliding => {
+            let mut latest_bindings = Vec::new();
+
+            for window_result in executor.execute_sliding_windows(window, sparql_query) {
+                if shutdown_rx.try_recv().is_ok() {
+                    return Ok(Vec::new());
+                }
+                latest_bindings = window_result?;
+            }
+
+            Ok(latest_bindings)
+        }
+        WindowType::Live => Err(JanusApiError::ExecutionError(format!(
+            "Generated baseline query cannot execute on live window '{}'",
+            window.window_name
+        ))),
+    }
+}
+
 fn collect_sliding_window_baseline_statements(
     executor: &HistoricalExecutor,
     window: &crate::parsing::janusql_parser::WindowDefinition,
@@ -670,6 +772,59 @@ fn collect_sliding_window_baseline_statements(
     Ok(baseline_statements_from_accumulator(&accumulator))
 }
 
+fn materialize_query_defined_baseline_quads(
+    parsed: &crate::parsing::janusql_parser::ParsedJanusQuery,
+    bindings_by_name: &HashMap<String, Vec<HashMap<String, String>>>,
+) -> Result<Vec<Quad>, JanusApiError> {
+    let mut materialized = Vec::new();
+    let mut seen = HashSet::new();
+
+    for baseline_use in &parsed.ast.baseline_uses {
+        if !seen.insert(baseline_use.name.clone()) {
+            continue;
+        }
+
+        // The GRAPH template is the materialization contract. We use it instead of
+        // SELECT alias heuristics because the template explicitly states the RDF
+        // shape that should be injected into the live static store.
+        let definition = parsed
+            .ast
+            .baseline_definitions
+            .iter()
+            .find(|definition| definition.name == baseline_use.name)
+            .ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "USING BASELINE references missing baseline definition '{}'",
+                    baseline_use.name
+                ))
+            })?;
+        let bindings = bindings_by_name.get(&baseline_use.name).ok_or_else(|| {
+            JanusApiError::ExecutionError(format!(
+                "USING BASELINE references missing evaluated baseline '{}'",
+                baseline_use.name
+            ))
+        })?;
+        let template = parsed
+            .baseline_graph_templates
+            .iter()
+            .find(|template| template.baseline_name == baseline_use.name)
+            .ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "USING BASELINE '{}' requires a matching GRAPH reference in the live query",
+                    baseline_use.name
+                ))
+            })?;
+        materialized.extend(materialize_baseline_bindings_as_quads(
+            &baseline_use.name,
+            definition,
+            template,
+            bindings,
+        )?);
+    }
+
+    Ok(materialized)
+}
+
 #[cfg(test)]
 fn materialize_bindings_as_static_baseline(
     processor: &mut LiveStreamProcessing,
@@ -679,6 +834,16 @@ fn materialize_bindings_as_static_baseline(
     materialize_static_baseline_statements(processor, &statements)
 }
 
+fn materialize_static_quads(
+    processor: &mut LiveStreamProcessing,
+    quads: &[Quad],
+) -> Result<(), JanusApiError> {
+    for quad in quads {
+        processor.add_static_quad(quad.clone());
+    }
+    Ok(())
+}
+
 fn materialize_static_baseline_statements(
     processor: &mut LiveStreamProcessing,
     statements: &[(String, String, String)],
@@ -696,6 +861,32 @@ fn materialize_static_baseline_statements(
     Ok(())
 }
 
+fn materialize_baseline_bindings_as_quads(
+    baseline_name: &str,
+    baseline_definition: &crate::parsing::janusql_parser::BaselineDefinition,
+    baseline_graph_template: &BaselineGraphTemplate,
+    bindings: &[HashMap<String, String>],
+) -> Result<Vec<Quad>, JanusApiError> {
+    let graph_name = GraphName::NamedNode(NamedNode::new(baseline_name).map_err(|e| {
+        JanusApiError::ExecutionError(format!(
+            "Invalid baseline graph name '{}': {}",
+            baseline_name, e
+        ))
+    })?);
+
+    let mut quads = Vec::new();
+    for binding in bindings {
+        for triple in &baseline_graph_template.triples {
+            let subject = resolve_subject_template_term(baseline_name, triple, binding)?;
+            let predicate = resolve_predicate_template_term(baseline_name, triple, binding)?;
+            let object = resolve_object_template_term(baseline_name, triple, binding)?;
+            quads.push(Quad::new(subject, predicate, object, graph_name.clone()));
+        }
+    }
+
+    Ok(quads)
+}
+
 fn baseline_statements_from_bindings(
     bindings: &[HashMap<String, String>],
 ) -> Vec<(String, String, String)> {
@@ -791,6 +982,263 @@ fn select_binding_anchor(binding: &HashMap<String, String>) -> Option<(String, S
         .find_map(|(name, raw)| normalize_iri_term(raw).map(|value| (name.clone(), value)))
 }
 
+fn validate_query_defined_baseline_access(
+    parsed: &crate::parsing::janusql_parser::ParsedJanusQuery,
+) -> Result<(), JanusApiError> {
+    for baseline_use in &parsed.ast.baseline_uses {
+        let template = parsed
+            .baseline_graph_templates
+            .iter()
+            .find(|template| template.baseline_name == baseline_use.name)
+            .ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "USING BASELINE '{}' requires a matching GRAPH reference in the live query",
+                    baseline_use.name
+                ))
+            })?;
+        let definition = parsed
+            .ast
+            .baseline_definitions
+            .iter()
+            .find(|definition| definition.name == baseline_use.name)
+            .ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "USING BASELINE references missing baseline definition '{}'",
+                    baseline_use.name
+                ))
+            })?;
+        validate_baseline_graph_template(definition, template)?;
+    }
+
+    Ok(())
+}
+
+fn validate_baseline_graph_template(
+    baseline_definition: &crate::parsing::janusql_parser::BaselineDefinition,
+    baseline_graph_template: &BaselineGraphTemplate,
+) -> Result<(), JanusApiError> {
+    let output_variables = baseline_definition
+        .output_variables
+        .iter()
+        .map(|variable| variable.trim_start_matches('?'))
+        .collect::<HashSet<_>>();
+
+    for triple in &baseline_graph_template.triples {
+        for term in [&triple.subject, &triple.object] {
+            if let GraphTermTemplate::Variable(variable_name) = term {
+                if !output_variables.contains(variable_name.as_str()) {
+                    return Err(JanusApiError::ExecutionError(format!(
+                        "GRAPH template for baseline '{}' references variable '?{}' that is not produced by the baseline SELECT output",
+                        baseline_graph_template.baseline_name,
+                        variable_name
+                    )));
+                }
+            }
+        }
+
+        if let GraphTermTemplate::Variable(variable_name) = &triple.predicate {
+            return Err(JanusApiError::ExecutionError(format!(
+                "GRAPH template for baseline '{}' uses variable predicate '?{}', but predicates must be concrete IRIs for now",
+                baseline_graph_template.baseline_name,
+                variable_name
+            )));
+        }
+    }
+
+    Ok(())
+}
+
+fn resolve_subject_template_term(
+    baseline_name: &str,
+    triple: &TripleTemplate,
+    binding: &HashMap<String, String>,
+) -> Result<NamedOrBlankNode, JanusApiError> {
+    match &triple.subject {
+        GraphTermTemplate::Variable(variable_name) => {
+            let raw_value = binding.get(variable_name).ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "Baseline '{}' binding is missing GRAPH template variable '?{}'",
+                    baseline_name, variable_name
+                ))
+            })?;
+            parse_subject_term(raw_value).map_err(|e| {
+                JanusApiError::ExecutionError(format!(
+                    "Failed to materialize baseline '{}' subject from variable '?{}' with value '{}': {}",
+                    baseline_name, variable_name, raw_value, e
+                ))
+            })
+        }
+        GraphTermTemplate::Iri(iri) => parse_named_or_blank_node(iri).map_err(|e| {
+            JanusApiError::ExecutionError(format!(
+                "Failed to materialize baseline '{}' subject IRI '{}': {}",
+                baseline_name, iri, e
+            ))
+        }),
+        GraphTermTemplate::Literal(raw_literal) => Err(JanusApiError::ExecutionError(format!(
+            "GRAPH template for baseline '{}' has a literal subject '{}', but subjects must be IRIs or blank nodes",
+            baseline_name, raw_literal
+        ))),
+    }
+}
+
+fn resolve_predicate_template_term(
+    baseline_name: &str,
+    triple: &TripleTemplate,
+    binding: &HashMap<String, String>,
+) -> Result<NamedNode, JanusApiError> {
+    match &triple.predicate {
+        GraphTermTemplate::Iri(iri) => NamedNode::new(iri.clone()).map_err(|e| {
+            JanusApiError::ExecutionError(format!(
+                "Failed to materialize baseline '{}' predicate '{}': {}",
+                baseline_name, iri, e
+            ))
+        }),
+        GraphTermTemplate::Variable(variable_name) => {
+            let _ = binding;
+            Err(JanusApiError::ExecutionError(format!(
+                "GRAPH template for baseline '{}' uses variable predicate '?{}', but predicates must be concrete IRIs for now",
+                baseline_name, variable_name
+            )))
+        }
+        GraphTermTemplate::Literal(raw_literal) => Err(JanusApiError::ExecutionError(format!(
+            "GRAPH template for baseline '{}' has a literal predicate '{}', but predicates must be IRIs",
+            baseline_name, raw_literal
+        ))),
+    }
+}
+
+fn resolve_object_template_term(
+    baseline_name: &str,
+    triple: &TripleTemplate,
+    binding: &HashMap<String, String>,
+) -> Result<Term, JanusApiError> {
+    match &triple.object {
+        GraphTermTemplate::Variable(variable_name) => {
+            let raw_value = binding.get(variable_name).ok_or_else(|| {
+                JanusApiError::ExecutionError(format!(
+                    "Baseline '{}' binding is missing GRAPH template variable '?{}'",
+                    baseline_name, variable_name
+                ))
+            })?;
+            parse_term(raw_value).map_err(|e| {
+                JanusApiError::ExecutionError(format!(
+                    "Failed to materialize baseline '{}' object from variable '?{}' with value '{}': {}",
+                    baseline_name, variable_name, raw_value, e
+                ))
+            })
+        }
+        GraphTermTemplate::Iri(iri) => parse_term(iri).map_err(|e| {
+            JanusApiError::ExecutionError(format!(
+                "Failed to materialize baseline '{}' object IRI '{}': {}",
+                baseline_name, iri, e
+            ))
+        }),
+        GraphTermTemplate::Literal(raw_literal) => {
+            parse_literal_term(raw_literal).map(Term::Literal).map_err(|e| {
+                JanusApiError::ExecutionError(format!(
+                    "Failed to materialize baseline '{}' literal object '{}': {}",
+                    baseline_name, raw_literal, e
+                ))
+            })
+        }
+    }
+}
+
+fn parse_subject_term(raw: &str) -> Result<NamedOrBlankNode, String> {
+    parse_named_or_blank_node(raw)
+}
+
+fn parse_term(raw: &str) -> Result<Term, String> {
+    if let Some(blank_node) = normalize_blank_node_term(raw) {
+        return BlankNode::new(blank_node).map(Term::BlankNode).map_err(|e| e.to_string());
+    }
+    if let Some(iri) = normalize_iri_term(raw) {
+        return NamedNode::new(iri).map(Term::NamedNode).map_err(|e| e.to_string());
+    }
+
+    parse_literal_term(raw).map(Term::Literal)
+}
+
+fn parse_named_or_blank_node(raw: &str) -> Result<NamedOrBlankNode, String> {
+    if let Some(blank_node) = normalize_blank_node_term(raw) {
+        return BlankNode::new(blank_node)
+            .map(NamedOrBlankNode::BlankNode)
+            .map_err(|e| e.to_string());
+    }
+    if let Some(iri) = normalize_iri_term(raw) {
+        return NamedNode::new(iri).map(NamedOrBlankNode::NamedNode).map_err(|e| e.to_string());
+    }
+    Err(format!("expected IRI or blank node subject but found {}", raw.trim()))
+}
+
+fn parse_literal_term(raw: &str) -> Result<Literal, String> {
+    let trimmed = raw.trim();
+    if !trimmed.starts_with('"') {
+        if trimmed.parse::<i64>().is_ok() {
+            return Ok(Literal::new_typed_literal(
+                trimmed,
+                NamedNode::new("http://www.w3.org/2001/XMLSchema#integer").unwrap(),
+            ));
+        }
+        if trimmed.parse::<f64>().is_ok() {
+            return Ok(Literal::new_typed_literal(
+                trimmed,
+                NamedNode::new("http://www.w3.org/2001/XMLSchema#decimal").unwrap(),
+            ));
+        }
+        return Ok(Literal::new_simple_literal(trimmed));
+    }
+
+    let (lexical, suffix) = split_literal_lexical_and_suffix(trimmed)?;
+    let lexical = unescape_literal_lexical(lexical);
+
+    if let Some(language) = suffix.strip_prefix('@') {
+        return Ok(
+            Literal::new_language_tagged_literal(lexical, language).map_err(|e| e.to_string())?
+        );
+    }
+
+    if let Some(datatype_iri) = suffix.strip_prefix("^^") {
+        let datatype = if datatype_iri.starts_with('<') && datatype_iri.ends_with('>') {
+            &datatype_iri[1..datatype_iri.len() - 1]
+        } else {
+            datatype_iri
+        };
+        return Ok(Literal::new_typed_literal(
+            lexical,
+            NamedNode::new(datatype).map_err(|e| e.to_string())?,
+        ));
+    }
+
+    Ok(Literal::new_simple_literal(lexical))
+}
+
+fn split_literal_lexical_and_suffix(raw: &str) -> Result<(&str, &str), String> {
+    let mut escaped = false;
+
+    for (index, ch) in raw.char_indices().skip(1) {
+        if escaped {
+            escaped = false;
+            continue;
+        }
+
+        match ch {
+            '\\' => escaped = true,
+            '"' => return Ok((&raw[1..index], raw[index + 1..].trim())),
+            _ => {}
+        }
+    }
+
+    Err(format!("invalid RDF literal '{}'", raw))
+}
+
+fn unescape_literal_lexical(raw: &str) -> String {
+    raw.replace("\\\"", "\"")
+        .replace("\\\\", "\\")
+        .replace("\\n", "\n")
+        .replace("\\t", "\t")
+}
+
 fn normalize_binding_term(raw: &str) -> String {
     normalize_iri_term(raw)
         .or_else(|| normalize_literal_term(raw))
@@ -808,6 +1256,11 @@ fn normalize_iri_term(raw: &str) -> Option<String> {
     }
 }
 
+fn normalize_blank_node_term(raw: &str) -> Option<String> {
+    let trimmed = raw.trim();
+    trimmed.strip_prefix("_:").map(str::to_string)
+}
+
 fn normalize_literal_term(raw: &str) -> Option<String> {
     let trimmed = raw.trim();
     if !trimmed.starts_with('"') {
@@ -886,11 +1339,27 @@ fn parse_mqtt_uri(stream_uri: &str) -> (String, u16, String) {
 #[cfg(test)]
 mod tests {
     use super::{
-        baseline_statements_from_bindings, materialize_bindings_as_static_baseline,
-        normalize_binding_term, parse_mqtt_uri, JANUS_BASELINE_NS,
+        baseline_statements_from_bindings, collect_query_defined_baseline_bindings,
+        materialize_baseline_bindings_as_quads, materialize_bindings_as_static_baseline,
+        normalize_binding_term, parse_mqtt_uri, validate_baseline_graph_template,
+        JANUS_BASELINE_NS,
+    };
+    use crate::{
+        core::RDFEvent,
+        parsing::janusql_parser::{
+            BaselineDefinition, BaselineGraphTemplate, GraphTermTemplate, JanusQLParser,
+            TripleTemplate,
+        },
+        storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
+        stream::live_stream_processing::LiveStreamProcessing,
+    };
+    use oxigraph::model::{GraphName, Literal, NamedNode, NamedOrBlankNode, Quad, Term};
+    use std::{
+        collections::HashMap,
+        sync::{mpsc, Arc},
+        thread,
+        time::Duration,
     };
-    use crate::{core::RDFEvent, stream::live_stream_processing::LiveStreamProcessing};
-    use std::{collections::HashMap, thread, time::Duration};
 
     #[test]
     fn test_parse_mqtt_uri_with_port() {
@@ -945,6 +1414,299 @@ mod tests {
         );
     }
 
+    #[test]
+    fn test_materialize_query_defined_baseline_bindings_as_quads() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor (AVG(?value) AS ?dayAvgValue)".to_string(),
+            where_clause: "WHERE { ?sensor <http://example.org/hasValue> ?value . }".to_string(),
+            group_by_clause: Some("GROUP BY ?sensor".to_string()),
+            output_variables: vec!["?sensor".to_string(), "?dayAvgValue".to_string()],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "<http://example.org/s1>".to_string()),
+            (
+                "dayAvgValue".to_string(),
+                "\"42.0\"^^<http://www.w3.org/2001/XMLSchema#decimal>".to_string(),
+            ),
+        ])];
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Iri("http://example.org/dayAvgValue".to_string()),
+                object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+            }],
+        };
+
+        let quads = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect("baseline quads should materialize");
+
+        assert_eq!(
+            quads,
+            vec![Quad::new(
+                NamedOrBlankNode::NamedNode(NamedNode::new("http://example.org/s1").unwrap()),
+                NamedNode::new("http://example.org/dayAvgValue").unwrap(),
+                Term::Literal(Literal::new_typed_literal(
+                    "42.0",
+                    NamedNode::new("http://www.w3.org/2001/XMLSchema#decimal").unwrap(),
+                )),
+                GraphName::NamedNode(NamedNode::new("http://example.org/dayBaseline").unwrap()),
+            )]
+        );
+    }
+
+    #[test]
+    fn test_materialize_query_defined_baseline_preserves_string_and_language_literals() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor ?label ?note".to_string(),
+            where_clause: "WHERE { ?sensor ?p ?o . }".to_string(),
+            group_by_clause: None,
+            output_variables: vec![
+                "?sensor".to_string(),
+                "?label".to_string(),
+                "?note".to_string(),
+            ],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "<http://example.org/s1>".to_string()),
+            ("label".to_string(), "\"pump\"".to_string()),
+            ("note".to_string(), "\"bonjour\"@fr".to_string()),
+        ])];
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![
+                TripleTemplate {
+                    subject: GraphTermTemplate::Variable("sensor".to_string()),
+                    predicate: GraphTermTemplate::Iri("http://example.org/label".to_string()),
+                    object: GraphTermTemplate::Variable("label".to_string()),
+                },
+                TripleTemplate {
+                    subject: GraphTermTemplate::Variable("sensor".to_string()),
+                    predicate: GraphTermTemplate::Iri("http://example.org/note".to_string()),
+                    object: GraphTermTemplate::Variable("note".to_string()),
+                },
+            ],
+        };
+
+        let quads = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect("baseline quads should materialize");
+
+        assert_eq!(quads.len(), 2);
+        assert!(quads.iter().any(|quad| quad.predicate.as_str() == "http://example.org/label"
+            && quad.object == Term::Literal(Literal::new_simple_literal("pump"))));
+        assert!(quads.iter().any(|quad| quad.predicate.as_str() == "http://example.org/note"
+            && quad.object
+                == Term::Literal(Literal::new_language_tagged_literal("bonjour", "fr").unwrap())));
+    }
+
+    #[test]
+    fn test_materialize_query_defined_baseline_rejects_non_iri_subject() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor (AVG(?value) AS ?dayAvgValue)".to_string(),
+            where_clause: "WHERE { ?sensor ?p ?value . }".to_string(),
+            group_by_clause: None,
+            output_variables: vec!["?sensor".to_string(), "?dayAvgValue".to_string()],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Iri("http://example.org/dayAvgValue".to_string()),
+                object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+            }],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "\"not-an-iri\"".to_string()),
+            (
+                "dayAvgValue".to_string(),
+                "\"42.0\"^^<http://www.w3.org/2001/XMLSchema#decimal>".to_string(),
+            ),
+        ])];
+
+        let err = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect_err("materialization should fail for non-IRI subject");
+
+        assert!(err.to_string().contains("expected IRI or blank node subject"));
+    }
+
+    #[test]
+    fn test_validate_query_defined_baseline_rejects_missing_template_variable() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor (AVG(?value) AS ?dayAvgValue)".to_string(),
+            where_clause: "WHERE { ?sensor ?p ?value . }".to_string(),
+            group_by_clause: Some("GROUP BY ?sensor".to_string()),
+            output_variables: vec!["?sensor".to_string(), "?dayAvgValue".to_string()],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Iri("http://example.org/dayCount".to_string()),
+                object: GraphTermTemplate::Variable("dayCount".to_string()),
+            }],
+        };
+
+        let err = validate_baseline_graph_template(&definition, &template)
+            .expect_err("validation should fail when template variable is absent");
+        assert!(err.to_string().contains("references variable '?dayCount' that is not produced"));
+    }
+
+    #[test]
+    fn test_validate_query_defined_baseline_rejects_variable_predicate() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor ?pred ?dayAvgValue".to_string(),
+            where_clause: "WHERE { ?sensor ?pred ?dayAvgValue . }".to_string(),
+            group_by_clause: None,
+            output_variables: vec![
+                "?sensor".to_string(),
+                "?pred".to_string(),
+                "?dayAvgValue".to_string(),
+            ],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Variable("pred".to_string()),
+                object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+            }],
+        };
+
+        let err = validate_baseline_graph_template(&definition, &template)
+            .expect_err("variable predicate should be rejected");
+        assert!(err.to_string().contains("predicates must be concrete IRIs"));
+    }
+
+    #[test]
+    fn test_materialize_query_defined_baseline_uses_multiple_template_triples() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor ?dayAvgValue ?dayCount".to_string(),
+            where_clause: "WHERE { ?sensor ?p ?o . }".to_string(),
+            group_by_clause: None,
+            output_variables: vec![
+                "?sensor".to_string(),
+                "?dayAvgValue".to_string(),
+                "?dayCount".to_string(),
+            ],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![
+                TripleTemplate {
+                    subject: GraphTermTemplate::Variable("sensor".to_string()),
+                    predicate: GraphTermTemplate::Iri("http://example.org/dayAvgValue".to_string()),
+                    object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+                },
+                TripleTemplate {
+                    subject: GraphTermTemplate::Variable("sensor".to_string()),
+                    predicate: GraphTermTemplate::Iri("http://example.org/dayCount".to_string()),
+                    object: GraphTermTemplate::Variable("dayCount".to_string()),
+                },
+            ],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "<http://example.org/s1>".to_string()),
+            (
+                "dayAvgValue".to_string(),
+                "\"42.0\"^^<http://www.w3.org/2001/XMLSchema#decimal>".to_string(),
+            ),
+            (
+                "dayCount".to_string(),
+                "\"10\"^^<http://www.w3.org/2001/XMLSchema#integer>".to_string(),
+            ),
+        ])];
+
+        let quads = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect("template materialization should succeed");
+
+        assert_eq!(quads.len(), 2);
+        assert!(quads
+            .iter()
+            .any(|quad| quad.predicate.as_str() == "http://example.org/dayAvgValue"));
+        assert!(quads
+            .iter()
+            .any(|quad| quad.predicate.as_str() == "http://example.org/dayCount"));
+    }
+
+    #[test]
+    fn test_materialize_query_defined_baseline_uses_template_predicate_not_variable_name() {
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor ?dayAvgValue".to_string(),
+            where_clause: "WHERE { ?sensor ?p ?o . }".to_string(),
+            group_by_clause: None,
+            output_variables: vec!["?sensor".to_string(), "?dayAvgValue".to_string()],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Iri(
+                    "http://example.org/customBaselineValue".to_string(),
+                ),
+                object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+            }],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "<http://example.org/s1>".to_string()),
+            (
+                "dayAvgValue".to_string(),
+                "\"42.0\"^^<http://www.w3.org/2001/XMLSchema#decimal>".to_string(),
+            ),
+        ])];
+
+        let quads = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect("template materialization should succeed");
+
+        assert_eq!(quads.len(), 1);
+        assert_eq!(quads[0].predicate.as_str(), "http://example.org/customBaselineValue");
+    }
+
     #[test]
     fn test_materialized_baseline_static_data_can_drive_live_extension_functions() {
         let query = format!(
@@ -1071,4 +1833,169 @@ mod tests {
             )]
         );
     }
+
+    #[test]
+    fn test_query_defined_baselines_are_evaluated_over_historical_windows() {
+        let config = StreamingConfig {
+            segment_base_path: format!(
+                "./test_data/janus_api_query_defined_baselines_{}",
+                std::time::SystemTime::now()
+                    .duration_since(std::time::UNIX_EPOCH)
+                    .unwrap()
+                    .as_millis()
+            ),
+            ..StreamingConfig::default()
+        };
+        let storage =
+            StreamingSegmentedStorage::new(config).expect("Failed to create segmented storage");
+
+        for i in 1..=10 {
+            storage
+                .write_rdf(
+                    i * 100,
+                    "http://example.org/sensor1",
+                    "http://example.org/temperature",
+                    &(20 + i).to_string(),
+                    "http://example.org/sensors",
+                )
+                .expect("Failed to write RDF event");
+        }
+        storage.flush().expect("Failed to flush storage");
+
+        let parser = JanusQLParser::new().expect("Failed to create parser");
+        let parsed = parser
+            .parse(
+                r#"
+PREFIX ex: <http://example.org/>
+
+FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [START 0 END 6000]
+
+DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+       (COUNT(?value) AS ?dayCount)
+WHERE {
+  ?sensor ex:temperature ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream ex:output AS
+USING BASELINE ex:dayBaseline
+SELECT ?sensor
+WHERE {
+  WINDOW ex:liveMinute {
+    ?sensor ex:temperature ?value .
+  }
+}
+GROUP BY ?sensor
+                "#,
+            )
+            .expect("Failed to parse JanusQL query");
+
+        let (_shutdown_tx, shutdown_rx) = mpsc::channel::<()>();
+        let bindings =
+            collect_query_defined_baseline_bindings(&Arc::new(storage), &parsed, &shutdown_rx)
+                .expect("Failed to evaluate query-defined baselines");
+
+        let day_baseline = bindings
+            .get("http://example.org/dayBaseline")
+            .expect("expected dayBaseline bindings");
+        assert_eq!(day_baseline.len(), 1);
+        assert!(day_baseline[0].contains_key("sensor"));
+        assert!(day_baseline[0].contains_key("dayAvgValue"));
+        assert!(day_baseline[0].contains_key("dayCount"));
+    }
+
+    #[test]
+    fn test_query_defined_baseline_static_graph_can_drive_live_group_by_having() {
+        let query = r#"
+            PREFIX : <http://example.org/>
+            REGISTER RStream :output AS
+            SELECT ?sensor
+                   (AVG(?value) AS ?minuteAvgValue)
+                   ?dayAvgValue
+                   ((AVG(?value) - ?dayAvgValue) AS ?difference)
+            FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60 STEP 5]
+            WHERE {
+                WINDOW :liveMinute {
+                    ?sensor :hasValue ?value .
+                }
+                GRAPH :dayBaseline {
+                    ?sensor :dayAvgValue ?dayAvgValue .
+                }
+            }
+            GROUP BY ?sensor ?dayAvgValue
+            HAVING(AVG(?value) > ?dayAvgValue)
+        "#;
+        let definition = BaselineDefinition {
+            name: "http://example.org/dayBaseline".to_string(),
+            source_window: "http://example.org/historyDay".to_string(),
+            raw_query: String::new(),
+            select_clause: "SELECT ?sensor (AVG(?value) AS ?dayAvgValue)".to_string(),
+            where_clause: "WHERE { ?sensor :hasValue ?value . }".to_string(),
+            group_by_clause: Some("GROUP BY ?sensor".to_string()),
+            output_variables: vec!["?sensor".to_string(), "?dayAvgValue".to_string()],
+        };
+        let template = BaselineGraphTemplate {
+            baseline_name: "http://example.org/dayBaseline".to_string(),
+            triples: vec![TripleTemplate {
+                subject: GraphTermTemplate::Variable("sensor".to_string()),
+                predicate: GraphTermTemplate::Iri("http://example.org/dayAvgValue".to_string()),
+                object: GraphTermTemplate::Variable("dayAvgValue".to_string()),
+            }],
+        };
+        let bindings = vec![HashMap::from([
+            ("sensor".to_string(), "<http://example.org/s1>".to_string()),
+            (
+                "dayAvgValue".to_string(),
+                "\"25\"^^<http://www.w3.org/2001/XMLSchema#decimal>".to_string(),
+            ),
+        ])];
+        let prefixes = HashMap::from([("".to_string(), "http://example.org/".to_string())]);
+
+        let quads = materialize_baseline_bindings_as_quads(
+            "http://example.org/dayBaseline",
+            &definition,
+            &template,
+            &bindings,
+        )
+        .expect("baseline quads should materialize");
+
+        let mut processor = LiveStreamProcessing::new(query.to_string()).unwrap();
+        processor.register_stream("http://example.org/stream").unwrap();
+        for quad in quads {
+            processor.add_static_quad(quad);
+        }
+        processor.start_processing().unwrap();
+        processor
+            .add_events(
+                "http://example.org/stream",
+                vec![
+                    RDFEvent::new(
+                        1,
+                        "http://example.org/s1",
+                        "http://example.org/hasValue",
+                        "30",
+                        "",
+                    ),
+                    RDFEvent::new(
+                        2,
+                        "http://example.org/s1",
+                        "http://example.org/hasValue",
+                        "32",
+                        "",
+                    ),
+                ],
+            )
+            .unwrap();
+        processor.close_stream("http://example.org/stream", 100).unwrap();
+        thread::sleep(Duration::from_millis(300));
+
+        let results = processor.collect_results(None).unwrap();
+        assert!(!results.is_empty(), "expected live result with baseline graph join");
+        let rendered = format!("{:?}", results);
+        assert!(rendered.contains("dayAvgValue"));
+        assert!(rendered.contains("difference"));
+    }
 }
diff --git a/src/bin/paper_historical_range_comparison.rs b/src/bin/paper_historical_range_comparison.rs
new file mode 100644
index 0000000..3f16e43
--- /dev/null
+++ b/src/bin/paper_historical_range_comparison.rs
@@ -0,0 +1,85 @@
+use clap::Parser;
+use janus::paper_bench::cli_output::{
+    default_benchmark_output_dir, print_benchmark_stdout, print_verbose_rows, BenchmarkArtifact,
+};
+use janus::paper_bench::historical_range::{
+    run_historical_range_comparison, HistoricalRangeComparisonConfig, HistoricalRangeMode,
+    HistoricalRangeQueryCase, HistoricalRangeQueryCaseArg, DEFAULT_DATASET_SIZES,
+    DEFAULT_FIXED_RANGE_SECONDS, FIXED_60S_PLOT_FILE, FULL_HISTORY_PLOT_FILE, RESULT_MARKDOWN_FILE,
+};
+use std::path::PathBuf;
+
+#[derive(Debug, Parser)]
+struct Args {
+    #[arg(long, default_value_t = 3)]
+    runs: usize,
+    #[arg(long, default_value_t = 1)]
+    warmup_runs: usize,
+    #[arg(long, value_delimiter = ',', default_values_t = DEFAULT_DATASET_SIZES.to_vec())]
+    dataset_sizes: Vec<usize>,
+    #[arg(
+        long,
+        value_delimiter = ',',
+        value_enum,
+        default_values_t = vec![
+            HistoricalRangeQueryCaseArg::Fixed60s,
+            HistoricalRangeQueryCaseArg::FullHistory
+        ]
+    )]
+    query_cases: Vec<HistoricalRangeQueryCaseArg>,
+    #[arg(long, default_value_t = DEFAULT_FIXED_RANGE_SECONDS)]
+    fixed_range_seconds: u64,
+    #[arg(long, value_enum, default_value_t = HistoricalRangeMode::Warm)]
+    mode: HistoricalRangeMode,
+    #[arg(long, default_value_t = false)]
+    debug_equivalence: bool,
+    #[arg(long)]
+    output_dir: Option<PathBuf>,
+    #[arg(long)]
+    verbose: bool,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let args = Args::parse();
+    let output_dir = args
+        .output_dir
+        .clone()
+        .unwrap_or_else(|| default_benchmark_output_dir("paper_historical_range_comparison"));
+    let outcome = run_historical_range_comparison(&HistoricalRangeComparisonConfig {
+        runs: args.runs,
+        warmup_runs: args.warmup_runs,
+        dataset_sizes: args.dataset_sizes,
+        query_cases: args.query_cases.into_iter().map(HistoricalRangeQueryCase::from_arg).collect(),
+        fixed_range_seconds: args.fixed_range_seconds,
+        mode: args.mode,
+        debug_equivalence: args.debug_equivalence,
+        output_dir: output_dir.clone(),
+    })?;
+
+    let raw_jsonl_path = output_dir.join("paper_historical_range_comparison.raw.jsonl");
+    let summary_csv_path = output_dir.join("paper_historical_range_comparison.summary.csv");
+    let markdown_path = output_dir.join(RESULT_MARKDOWN_FILE);
+    let fixed_plot_path = output_dir.join(FIXED_60S_PLOT_FILE);
+    let full_plot_path = output_dir.join(FULL_HISTORY_PLOT_FILE);
+
+    print_benchmark_stdout(
+        "paper_historical_range_comparison",
+        Some(outcome.run_outcomes.iter().all(|run| run.equivalent)),
+        Some(args.warmup_runs),
+        Some(args.runs),
+        &output_dir,
+        &[
+            BenchmarkArtifact { label: "raw_jsonl", path: &raw_jsonl_path },
+            BenchmarkArtifact { label: "summary_csv", path: &summary_csv_path },
+            BenchmarkArtifact { label: "markdown", path: &markdown_path },
+            BenchmarkArtifact { label: "fixed_plot", path: &fixed_plot_path },
+            BenchmarkArtifact { label: "full_history_plot", path: &full_plot_path },
+        ],
+    );
+
+    if args.verbose {
+        print_verbose_rows(&outcome.run_outcomes)?;
+    }
+
+    Ok(())
+}
diff --git a/src/bin/paper_historical_scaling.rs b/src/bin/paper_historical_scaling.rs
new file mode 100644
index 0000000..1194bea
--- /dev/null
+++ b/src/bin/paper_historical_scaling.rs
@@ -0,0 +1,126 @@
+use clap::Parser;
+use janus::paper_bench::cli_output::{
+    default_benchmark_output_dir, print_benchmark_stdout, print_verbose_rows, BenchmarkArtifact,
+};
+use janus::paper_bench::harness::{
+    collect_repro_metadata, ensure_output_dir, fill_scaling_percentiles,
+    generate_citybench_dataset, run_scaling_query, summarize_scaling, summarize_scaling_fit,
+    write_jsonl, write_scaling_fit_csv, write_scaling_summary_csv, ExecutionMode,
+    HistoricalDataset, ScalingQueryType, ScalingRow, ScalingRunConfig,
+};
+use std::path::PathBuf;
+
+#[derive(Debug, Parser)]
+struct Args {
+    #[arg(long, default_value_t = 0)]
+    warmup_runs: usize,
+    #[arg(long, default_value_t = 5)]
+    runs: usize,
+    #[arg(long, default_value_t = false)]
+    include_warmups: bool,
+    #[arg(
+        long,
+        value_delimiter = ',',
+        default_values_t = vec![100_000usize, 500_000, 1_000_000, 5_000_000]
+    )]
+    dataset_sizes: Vec<usize>,
+    #[arg(
+        long,
+        value_delimiter = ',',
+        value_enum,
+        default_values_t = vec![
+            ScalingQueryType::PointLookup,
+            ScalingQueryType::FixedWindow,
+            ScalingQueryType::ProportionalRange10,
+            ScalingQueryType::ProportionalRange50,
+            ScalingQueryType::FullRange,
+            ScalingQueryType::HybridBaselineLookup,
+        ]
+    )]
+    query_types: Vec<ScalingQueryType>,
+    #[arg(long, value_enum, default_value_t = ExecutionMode::Warm)]
+    mode: ExecutionMode,
+    #[arg(long)]
+    output_dir: Option<PathBuf>,
+    #[arg(long)]
+    verbose: bool,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let args = Args::parse();
+    let output_dir = args
+        .output_dir
+        .clone()
+        .unwrap_or_else(|| default_benchmark_output_dir("paper_historical_scaling"));
+    ensure_output_dir(&output_dir)?;
+    let metadata = collect_repro_metadata();
+    let mut all_rows = Vec::<ScalingRow>::new();
+
+    for &dataset_size in &args.dataset_sizes {
+        let warm_dataset: Option<HistoricalDataset> = if args.mode == ExecutionMode::Warm {
+            Some(generate_citybench_dataset(dataset_size, &output_dir)?)
+        } else {
+            None
+        };
+
+        for &query_type in &args.query_types {
+            for run_index in 0..args.warmup_runs {
+                all_rows.push(run_scaling_query(ScalingRunConfig {
+                    mode: args.mode,
+                    dataset_size_quads: dataset_size,
+                    query_type,
+                    metadata: &metadata,
+                    run_index,
+                    is_warmup: true,
+                    warm_dataset: warm_dataset.as_ref(),
+                    output_dir: &output_dir,
+                })?);
+            }
+            for run_index in 0..args.runs {
+                all_rows.push(run_scaling_query(ScalingRunConfig {
+                    mode: args.mode,
+                    dataset_size_quads: dataset_size,
+                    query_type,
+                    metadata: &metadata,
+                    run_index,
+                    is_warmup: false,
+                    warm_dataset: warm_dataset.as_ref(),
+                    output_dir: &output_dir,
+                })?);
+            }
+        }
+    }
+
+    let mut output_rows = if args.include_warmups {
+        all_rows.clone()
+    } else {
+        all_rows.iter().filter(|row| !row.is_warmup).cloned().collect::<Vec<_>>()
+    };
+
+    fill_scaling_percentiles(&mut output_rows);
+    let jsonl_path = output_dir.join("paper_historical_scaling.raw.jsonl");
+    let csv_path = output_dir.join("paper_historical_scaling.summary.csv");
+    let fit_csv_path = output_dir.join("paper_historical_scaling.fit.csv");
+    write_jsonl(&jsonl_path, &output_rows)?;
+    write_scaling_summary_csv(&csv_path, &summarize_scaling(&output_rows))?;
+    write_scaling_fit_csv(&fit_csv_path, &summarize_scaling_fit(&output_rows))?;
+
+    print_benchmark_stdout(
+        "paper_historical_scaling",
+        None,
+        Some(args.warmup_runs),
+        Some(args.runs),
+        &output_dir,
+        &[
+            BenchmarkArtifact { label: "raw_jsonl", path: &jsonl_path },
+            BenchmarkArtifact { label: "summary_csv", path: &csv_path },
+            BenchmarkArtifact { label: "fit_csv", path: &fit_csv_path },
+        ],
+    );
+
+    if args.verbose {
+        print_verbose_rows(&output_rows)?;
+    }
+
+    Ok(())
+}
diff --git a/src/bin/paper_hybrid_coordination.rs b/src/bin/paper_hybrid_coordination.rs
new file mode 100644
index 0000000..e23c300
--- /dev/null
+++ b/src/bin/paper_hybrid_coordination.rs
@@ -0,0 +1,115 @@
+use clap::Parser;
+use janus::paper_bench::cli_output::{
+    default_benchmark_output_dir, print_benchmark_stdout, print_verbose_rows, BenchmarkArtifact,
+};
+use janus::paper_bench::{
+    external::OxigraphExternalAdapter,
+    harness::{
+        collect_repro_metadata, ensure_output_dir, prepare_coordination_workload,
+        run_coordination_pair, summarize_coordination, write_coordination_summary_csv, write_jsonl,
+        CoordinationRow, CoordinationRunConfig, ExecutionMode,
+    },
+};
+use std::path::PathBuf;
+
+#[derive(Debug, Parser)]
+struct Args {
+    #[arg(long, default_value_t = 0)]
+    warmup_runs: usize,
+    #[arg(long, default_value_t = 10)]
+    runs: usize,
+    #[arg(long, default_value_t = false)]
+    include_warmups: bool,
+    #[arg(long, default_value_t = false)]
+    debug_equivalence: bool,
+    #[arg(long, default_value_t = 10_000)]
+    historical_events: usize,
+    #[arg(long, default_value_t = 32)]
+    live_events: usize,
+    #[arg(long, value_enum, default_value_t = ExecutionMode::Warm)]
+    mode: ExecutionMode,
+    #[arg(long)]
+    output_dir: Option<PathBuf>,
+    #[arg(long)]
+    verbose: bool,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let args = Args::parse();
+    let output_dir = args
+        .output_dir
+        .clone()
+        .unwrap_or_else(|| default_benchmark_output_dir("paper_hybrid_coordination"));
+    ensure_output_dir(&output_dir)?;
+
+    let metadata = collect_repro_metadata();
+    let adapter = OxigraphExternalAdapter::new();
+    let warm_workload = if args.mode == ExecutionMode::Warm {
+        Some(prepare_coordination_workload(args.historical_events, args.live_events)?)
+    } else {
+        None
+    };
+
+    let mut all_rows = Vec::<CoordinationRow>::with_capacity((args.warmup_runs + args.runs) * 2);
+
+    for run_index in 0..args.warmup_runs {
+        let pair = run_coordination_pair(CoordinationRunConfig {
+            mode: args.mode,
+            run_index,
+            is_warmup: true,
+            historical_events: args.historical_events,
+            live_events: args.live_events,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: warm_workload.as_ref(),
+            debug_output_dir: args.debug_equivalence.then_some(output_dir.as_path()),
+        })?;
+        all_rows.push(pair.unified);
+        all_rows.push(pair.decomposed);
+    }
+
+    for run_index in 0..args.runs {
+        let pair = run_coordination_pair(CoordinationRunConfig {
+            mode: args.mode,
+            run_index,
+            is_warmup: false,
+            historical_events: args.historical_events,
+            live_events: args.live_events,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: warm_workload.as_ref(),
+            debug_output_dir: args.debug_equivalence.then_some(output_dir.as_path()),
+        })?;
+        all_rows.push(pair.unified);
+        all_rows.push(pair.decomposed);
+    }
+
+    let output_rows = if args.include_warmups {
+        all_rows.clone()
+    } else {
+        all_rows.iter().filter(|row| !row.is_warmup).cloned().collect::<Vec<_>>()
+    };
+
+    let jsonl_path = output_dir.join("paper_hybrid_coordination.raw.jsonl");
+    let csv_path = output_dir.join("paper_hybrid_coordination.summary.csv");
+    write_jsonl(&jsonl_path, &output_rows)?;
+    write_coordination_summary_csv(&csv_path, &summarize_coordination(&output_rows))?;
+
+    print_benchmark_stdout(
+        "paper_hybrid_coordination",
+        None,
+        Some(args.warmup_runs),
+        Some(args.runs),
+        &output_dir,
+        &[
+            BenchmarkArtifact { label: "raw_jsonl", path: &jsonl_path },
+            BenchmarkArtifact { label: "summary_csv", path: &csv_path },
+        ],
+    );
+
+    if args.verbose {
+        print_verbose_rows(&output_rows)?;
+    }
+
+    Ok(())
+}
diff --git a/src/bin/paper_query_defined_baseline.rs b/src/bin/paper_query_defined_baseline.rs
new file mode 100644
index 0000000..f1914af
--- /dev/null
+++ b/src/bin/paper_query_defined_baseline.rs
@@ -0,0 +1,178 @@
+use clap::Parser;
+use janus::paper_bench::cli_output::{print_benchmark_stdout, BenchmarkArtifact};
+use janus::paper_bench::query_defined_baseline::{
+    run_query_defined_baseline_benchmark, LiveReplayMode, QueryDefinedBaselineBenchmarkConfig,
+    QueryDefinedBaselineProfile,
+};
+use std::path::PathBuf;
+
+#[derive(Debug, Parser)]
+struct Args {
+    #[arg(long, default_value_t = 0)]
+    warmup_runs: usize,
+    #[arg(long, default_value_t = 1)]
+    runs: usize,
+    #[arg(long, value_delimiter = ',', default_values_t = [1000usize], value_parser = parse_historical_event_count)]
+    historical_events: Vec<usize>,
+    #[arg(long, value_delimiter = ',', default_values_t = [1usize])]
+    baseline_entities: Vec<usize>,
+    #[arg(long, value_enum, default_value_t = LiveReplayMode::Accelerated)]
+    live_replay_mode: LiveReplayMode,
+    #[arg(long, default_value_t = 4.0)]
+    live_rate_hz: f64,
+    #[arg(long)]
+    live_duration_seconds: Option<u64>,
+    #[arg(long)]
+    live_window_size_seconds: Option<u64>,
+    #[arg(long)]
+    live_window_slide_seconds: Option<u64>,
+    #[arg(long)]
+    output_dir: Option<PathBuf>,
+    #[arg(long, value_enum, default_value_t = QueryDefinedBaselineProfile::Smoke)]
+    profile: QueryDefinedBaselineProfile,
+    #[arg(long)]
+    debug_lowered_query: bool,
+    #[arg(long)]
+    verbose: bool,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let args = Args::parse();
+    let outcome = run_query_defined_baseline_benchmark(QueryDefinedBaselineBenchmarkConfig {
+        profile: args.profile,
+        runs: args.runs,
+        warmup_runs: args.warmup_runs,
+        historical_events: args.historical_events,
+        baseline_entities: args.baseline_entities,
+        live_replay_mode: args.live_replay_mode,
+        live_rate_hz: args.live_rate_hz,
+        live_duration_seconds: args.live_duration_seconds,
+        live_window_size_seconds: args.live_window_size_seconds,
+        live_window_slide_seconds: args.live_window_slide_seconds,
+        output_dir: args.output_dir,
+        debug_lowered_query: args.debug_lowered_query,
+        verbose: args.verbose,
+    })?;
+
+    print_benchmark_stdout(
+        "query_defined_baseline",
+        Some(outcome.report.correctness_passed),
+        Some(outcome.report.warmup_runs),
+        Some(outcome.report.runs),
+        &outcome.report.output_dir,
+        &[
+            BenchmarkArtifact { label: "raw_json", path: &outcome.report_path },
+            BenchmarkArtifact { label: "summary_csv", path: &outcome.summary_csv_path },
+            BenchmarkArtifact { label: "summary_md", path: &outcome.summary_md_path },
+        ],
+    );
+
+    if args.verbose {
+        for (index, comparison) in outcome.report.comparisons.iter().enumerate() {
+            let phase = if index < outcome.report.warmup_runs {
+                "warmup"
+            } else {
+                "measured"
+            };
+            println!(
+                "phase={} run={} mode={} baseline_first_result_ms={:.3} live_only_first_result_ms={:.3} baseline_results={} live_only_results={} baseline_emitted_windows={} live_only_emitted_windows={} observed_baseline_rows={} observed_live_only_rows={} expected_emitted_windows={} expected_full_windows={} warmup_window_count={} startup_overhead_ms={:.3} first_result_overhead_ms={:.3}",
+                phase,
+                comparison.run_index,
+                comparison.baseline.live_replay_mode,
+                comparison.baseline.first_result_latency_ms,
+                comparison.live_only.first_result_latency_ms,
+                comparison.baseline.result_count,
+                comparison.live_only.result_count,
+                comparison.baseline.observed_emitted_windows,
+                comparison.live_only.observed_emitted_windows,
+                comparison.observed_baseline_rows,
+                comparison.observed_live_only_rows,
+                comparison.baseline.expected_emitted_windows,
+                comparison.baseline.expected_full_windows,
+                comparison
+                    .baseline
+                    .warmup_window_count
+                    .map(|value| value.to_string())
+                    .unwrap_or_else(|| "-".to_string()),
+                comparison.live_startup_overhead_ms,
+                comparison.first_result_overhead_ms
+            );
+            if !comparison.baseline.completed_window_latencies_ms.is_empty() {
+                println!(
+                    "baseline_window_latencies_ms={:?}",
+                    comparison.baseline.completed_window_latencies_ms
+                );
+            }
+            if !comparison.live_only.completed_window_latencies_ms.is_empty() {
+                println!(
+                    "live_only_window_latencies_ms={:?}",
+                    comparison.live_only.completed_window_latencies_ms
+                );
+            }
+        }
+    }
+
+    Ok(())
+}
+
+fn parse_historical_event_count(raw: &str) -> Result<usize, String> {
+    let trimmed = raw.trim();
+    if trimmed.is_empty() {
+        return Err("historical event count cannot be empty".to_string());
+    }
+
+    let (digits, multiplier) = match trimmed.chars().last() {
+        Some('K') => (&trimmed[..trimmed.len() - 1], 1_000usize),
+        Some('M') => (&trimmed[..trimmed.len() - 1], 1_000_000usize),
+        _ => (trimmed, 1usize),
+    };
+
+    if digits.is_empty() {
+        return Err(format!("invalid historical event count '{raw}'"));
+    }
+
+    let base = digits
+        .parse::<usize>()
+        .map_err(|_| format!("invalid historical event count '{raw}'"))?;
+    base.checked_mul(multiplier)
+        .ok_or_else(|| format!("historical event count '{raw}' is too large"))
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn defaults_to_accelerated_live_replay() {
+        let args =
+            Args::try_parse_from(["paper_query_defined_baseline"]).expect("args should parse");
+        assert_eq!(args.live_replay_mode, LiveReplayMode::Accelerated);
+        assert!((args.live_rate_hz - 4.0).abs() < f64::EPSILON);
+        assert!(args.live_duration_seconds.is_none());
+        assert!(args.live_window_size_seconds.is_none());
+        assert!(args.live_window_slide_seconds.is_none());
+    }
+
+    #[test]
+    fn parses_realtime_live_replay_flags() {
+        let args = Args::try_parse_from([
+            "paper_query_defined_baseline",
+            "--live-replay-mode",
+            "realtime",
+            "--live-rate-hz",
+            "4",
+            "--live-duration-seconds",
+            "240",
+            "--live-window-size-seconds",
+            "120",
+            "--live-window-slide-seconds",
+            "60",
+        ])
+        .expect("args should parse");
+        assert_eq!(args.live_replay_mode, LiveReplayMode::Realtime);
+        assert!((args.live_rate_hz - 4.0).abs() < f64::EPSILON);
+        assert_eq!(args.live_duration_seconds, Some(240));
+        assert_eq!(args.live_window_size_seconds, Some(120));
+        assert_eq!(args.live_window_slide_seconds, Some(60));
+    }
+}
diff --git a/src/bin/paper_sustained_hybrid.rs b/src/bin/paper_sustained_hybrid.rs
new file mode 100644
index 0000000..1212bdd
--- /dev/null
+++ b/src/bin/paper_sustained_hybrid.rs
@@ -0,0 +1,166 @@
+use clap::Parser;
+use janus::paper_bench::cli_output::{
+    default_benchmark_output_dir, print_benchmark_stdout, print_verbose_rows, BenchmarkArtifact,
+};
+use janus::paper_bench::{
+    external::OxigraphExternalAdapter,
+    harness::{
+        collect_repro_metadata, ensure_output_dir, prepare_sustained_workload, run_sustained_pair,
+        summarize_sustained, sustained_event_interval_ms,
+        sustained_expected_wall_clock_duration_ms, write_jsonl, write_sustained_summary_csv,
+        ExecutionMode, SustainedRow, SustainedRunConfig, TimeMode,
+    },
+};
+use std::path::PathBuf;
+
+#[derive(Debug, Parser)]
+struct Args {
+    #[arg(long, default_value_t = 0)]
+    warmup_runs: usize,
+    #[arg(long, default_value_t = 10)]
+    runs: usize,
+    #[arg(long, default_value_t = false)]
+    include_warmups: bool,
+    #[arg(long, default_value_t = false)]
+    debug_equivalence: bool,
+    #[arg(long, default_value_t = 10_000)]
+    historical_events: usize,
+    #[arg(long, default_value_t = 240)]
+    live_duration_seconds: usize,
+    #[arg(long, default_value_t = 1)]
+    event_rate_hz: usize,
+    #[arg(long, default_value_t = 120)]
+    window_size_seconds: usize,
+    #[arg(long, default_value_t = 60)]
+    window_slide_seconds: usize,
+    #[arg(long, value_enum, default_value_t = ExecutionMode::Warm)]
+    mode: ExecutionMode,
+    #[arg(long, value_enum, default_value_t = TimeMode::Virtual)]
+    time_mode: TimeMode,
+    #[arg(long)]
+    output_dir: Option<PathBuf>,
+    #[arg(long)]
+    verbose: bool,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let args = Args::parse();
+    if args.event_rate_hz == 0 {
+        return Err("--event-rate-hz must be at least 1".into());
+    }
+    let event_interval_ms = sustained_event_interval_ms(args.event_rate_hz);
+    let expected_wall_clock_duration_ms =
+        sustained_expected_wall_clock_duration_ms(args.live_duration_seconds);
+    let output_dir = args
+        .output_dir
+        .clone()
+        .unwrap_or_else(|| default_benchmark_output_dir("paper_sustained_hybrid"));
+    ensure_output_dir(&output_dir)?;
+
+    let metadata = collect_repro_metadata();
+    let adapter = OxigraphExternalAdapter::new();
+    let warm_workload = if args.mode == ExecutionMode::Warm {
+        Some(prepare_sustained_workload(
+            args.historical_events,
+            args.live_duration_seconds,
+            args.event_rate_hz,
+            args.window_size_seconds,
+            args.window_slide_seconds,
+        )?)
+    } else {
+        None
+    };
+
+    let mut all_rows = Vec::<SustainedRow>::with_capacity((args.warmup_runs + args.runs) * 2);
+
+    for run_index in 0..args.warmup_runs {
+        let pair = run_sustained_pair(SustainedRunConfig {
+            mode: args.mode,
+            time_mode: args.time_mode,
+            run_index,
+            is_warmup: true,
+            historical_events: args.historical_events,
+            live_duration_seconds: args.live_duration_seconds,
+            event_rate_hz: args.event_rate_hz,
+            event_interval_ms,
+            expected_wall_clock_duration_ms,
+            window_size_seconds: args.window_size_seconds,
+            window_slide_seconds: args.window_slide_seconds,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: warm_workload.as_ref(),
+            debug_output_dir: args.debug_equivalence.then_some(output_dir.as_path()),
+        })?;
+        all_rows.push(pair.unified);
+        all_rows.push(pair.decomposed);
+    }
+
+    for run_index in 0..args.runs {
+        let pair = run_sustained_pair(SustainedRunConfig {
+            mode: args.mode,
+            time_mode: args.time_mode,
+            run_index,
+            is_warmup: false,
+            historical_events: args.historical_events,
+            live_duration_seconds: args.live_duration_seconds,
+            event_rate_hz: args.event_rate_hz,
+            event_interval_ms,
+            expected_wall_clock_duration_ms,
+            window_size_seconds: args.window_size_seconds,
+            window_slide_seconds: args.window_slide_seconds,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: warm_workload.as_ref(),
+            debug_output_dir: args.debug_equivalence.then_some(output_dir.as_path()),
+        })?;
+        all_rows.push(pair.unified);
+        all_rows.push(pair.decomposed);
+    }
+
+    let output_rows = if args.include_warmups {
+        all_rows.clone()
+    } else {
+        all_rows.iter().filter(|row| !row.is_warmup).cloned().collect::<Vec<_>>()
+    };
+
+    let jsonl_path = output_dir.join("paper_sustained_hybrid.raw.jsonl");
+    let csv_path = output_dir.join("paper_sustained_hybrid.summary.csv");
+    write_jsonl(&jsonl_path, &output_rows)?;
+    write_sustained_summary_csv(&csv_path, &summarize_sustained(&output_rows))?;
+
+    print_benchmark_stdout(
+        "paper_sustained_hybrid",
+        None,
+        Some(args.warmup_runs),
+        Some(args.runs),
+        &output_dir,
+        &[
+            BenchmarkArtifact { label: "raw_jsonl", path: &jsonl_path },
+            BenchmarkArtifact { label: "summary_csv", path: &csv_path },
+        ],
+    );
+
+    if args.verbose {
+        print_verbose_rows(&output_rows)?;
+    }
+
+    Ok(())
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn time_mode_defaults_to_virtual() {
+        let args = Args::try_parse_from(["paper_sustained_hybrid"]).expect("args should parse");
+        assert_eq!(args.time_mode, TimeMode::Virtual);
+    }
+
+    #[test]
+    fn time_mode_parses_wall_clock() {
+        let args = Args::try_parse_from(["paper_sustained_hybrid", "--time-mode", "wall-clock"])
+            .expect("args should parse");
+        assert_eq!(args.time_mode, TimeMode::WallClock);
+    }
+}
diff --git a/src/http/server.rs b/src/http/server.rs
index 953913e..9f8c28b 100644
--- a/src/http/server.rs
+++ b/src/http/server.rs
@@ -244,6 +244,12 @@ impl From<JanusApiError> for ApiError {
     }
 }
 
+fn schedule_stream_bus_drop(stream_bus: Arc<StreamBus>) {
+    std::thread::spawn(move || {
+        drop(stream_bus);
+    });
+}
+
 /// Create the HTTP server with all routes
 pub fn create_server(
     janus_api: Arc<JanusApi>,
@@ -604,37 +610,40 @@ async fn start_replay(
 
     let replay_state_clone = Arc::clone(&state.replay_state);
 
+    let old_stream_bus = replay_state.stream_bus.take();
+    replay_state.is_running = true;
+    replay_state.start_time = Some(Instant::now());
+    replay_state.input_file = Some(input_file_clone);
+    replay_state.stream_bus = Some(Arc::clone(&stream_bus));
+    replay_state.events_read = events_read;
+    replay_state.events_published = events_published;
+    replay_state.events_stored = events_stored;
+    replay_state.publish_errors = publish_errors;
+    replay_state.storage_errors = storage_errors;
+    drop(replay_state);
+
+    if let Some(bus) = old_stream_bus {
+        schedule_stream_bus_drop(bus);
+    }
+
     // Spawn replay in a blocking thread to avoid runtime conflict
     std::thread::spawn(move || {
         if let Err(e) = stream_bus_clone.start() {
             eprintln!("Stream bus replay error: {}", e);
         }
 
-        // Reset running state when finished
-        if let Ok(mut rs) = replay_state_clone.lock() {
+        let finished_bus = replay_state_clone.lock().ok().and_then(|mut rs| {
             rs.is_running = false;
             rs.start_time = None;
+            rs.input_file = None;
             println!("Stream bus replay finished");
-        }
-    });
-
-    // Safely drop the old stream_bus if it exists, to avoid dropping a Runtime in async context
-    let old_stream_bus = replay_state.stream_bus.take();
-    if let Some(bus) = old_stream_bus {
-        tokio::task::spawn_blocking(move || {
-            drop(bus);
+            rs.stream_bus.take()
         });
-    }
 
-    replay_state.is_running = true;
-    replay_state.start_time = Some(Instant::now());
-    replay_state.input_file = Some(input_file_clone);
-    replay_state.stream_bus = Some(stream_bus);
-    replay_state.events_read = events_read;
-    replay_state.events_published = events_published;
-    replay_state.events_stored = events_stored;
-    replay_state.publish_errors = publish_errors;
-    replay_state.storage_errors = storage_errors;
+        if let Some(bus) = finished_bus {
+            schedule_stream_bus_drop(bus);
+        }
+    });
 
     Ok(Json(SuccessResponse {
         message: format!("Stream bus replay started with file: {}", payload.input_file),
@@ -651,15 +660,18 @@ async fn stop_replay(
         return Err(ApiError::BadRequest("Replay is not running".to_string()));
     }
 
-    // Stop the stream bus if it exists
-    if let Some(stream_bus) = &replay_state.stream_bus {
-        stream_bus.stop();
+    let stream_bus = replay_state.stream_bus.take();
+    if let Some(bus) = stream_bus.as_ref() {
+        bus.stop();
     }
-
     replay_state.is_running = false;
     replay_state.start_time = None;
     replay_state.input_file = None;
-    replay_state.stream_bus = None;
+    drop(replay_state);
+
+    if let Some(bus) = stream_bus {
+        schedule_stream_bus_drop(bus);
+    }
 
     Ok(Json(SuccessResponse { message: "Stream bus replay stopped".to_string() }))
 }
diff --git a/src/lib.rs b/src/lib.rs
index 77b56f5..265549b 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -116,6 +116,7 @@ pub mod http;
 
 /// Janus-specific SPARQL extension functions.
 pub mod extensions;
+pub mod paper_bench;
 
 pub mod error {
     //! Error types and result definitions
diff --git a/src/paper_bench/cli_output.rs b/src/paper_bench/cli_output.rs
new file mode 100644
index 0000000..e831552
--- /dev/null
+++ b/src/paper_bench/cli_output.rs
@@ -0,0 +1,45 @@
+use serde::Serialize;
+use std::path::{Path, PathBuf};
+use std::time::{SystemTime, UNIX_EPOCH};
+
+pub struct BenchmarkArtifact<'a> {
+    pub label: &'a str,
+    pub path: &'a Path,
+}
+
+pub fn default_benchmark_output_dir(benchmark: &str) -> PathBuf {
+    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap_or_default().as_millis();
+    PathBuf::from(format!("logs/benchmark/{benchmark}/{ts}"))
+}
+
+pub fn print_benchmark_stdout(
+    benchmark: &str,
+    correctness_passed: Option<bool>,
+    warmup_runs: Option<usize>,
+    measured_runs: Option<usize>,
+    output_dir: &Path,
+    artifacts: &[BenchmarkArtifact<'_>],
+) {
+    println!("benchmark={benchmark}");
+    if let Some(correctness_passed) = correctness_passed {
+        println!("correctness_passed={correctness_passed}");
+    }
+    if warmup_runs.is_some() || measured_runs.is_some() {
+        println!(
+            "warmup_runs={} measured_runs={}",
+            warmup_runs.unwrap_or(0),
+            measured_runs.unwrap_or(0)
+        );
+    }
+    println!("output_dir={}", output_dir.display());
+    for artifact in artifacts {
+        println!("{}={}", artifact.label, artifact.path.display());
+    }
+}
+
+pub fn print_verbose_rows<T: Serialize>(rows: &[T]) -> Result<(), serde_json::Error> {
+    for row in rows {
+        println!("{}", serde_json::to_string(row)?);
+    }
+    Ok(())
+}
diff --git a/src/paper_bench/external.rs b/src/paper_bench/external.rs
new file mode 100644
index 0000000..715e36a
--- /dev/null
+++ b/src/paper_bench/external.rs
@@ -0,0 +1,89 @@
+use crate::core::RDFEvent;
+use crate::querying::oxigraph_adapter::OxigraphAdapter;
+use oxigraph::model::{GraphName, NamedNode, Quad, Term};
+use rsp_rs::QuadContainer;
+use std::collections::{HashMap, HashSet};
+
+pub type ExternalBindings = Vec<HashMap<String, String>>;
+
+pub trait ExternalHistoricalAdapter {
+    fn name(&self) -> &'static str;
+
+    fn execute_bindings_query(
+        &self,
+        query: &str,
+        events: &[RDFEvent],
+    ) -> Result<ExternalBindings, Box<dyn std::error::Error>>;
+}
+
+pub struct OxigraphExternalAdapter {
+    adapter: OxigraphAdapter,
+}
+
+impl OxigraphExternalAdapter {
+    pub fn new() -> Self {
+        Self { adapter: OxigraphAdapter::new() }
+    }
+}
+
+impl Default for OxigraphExternalAdapter {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl ExternalHistoricalAdapter for OxigraphExternalAdapter {
+    fn name(&self) -> &'static str {
+        "oxigraph"
+    }
+
+    fn execute_bindings_query(
+        &self,
+        query: &str,
+        events: &[RDFEvent],
+    ) -> Result<ExternalBindings, Box<dyn std::error::Error>> {
+        let mut quads = HashSet::with_capacity(events.len());
+        for event in events {
+            quads.insert(rdf_event_to_quad(event)?);
+        }
+        let container = QuadContainer::new(
+            quads,
+            events
+                .last()
+                .map_or(0_i64, |event| i64::try_from(event.timestamp).unwrap_or(i64::MAX)),
+        );
+        Ok(self.adapter.execute_query_bindings(query, &container)?)
+    }
+}
+
+pub struct JenaExternalAdapterStub;
+
+impl ExternalHistoricalAdapter for JenaExternalAdapterStub {
+    fn name(&self) -> &'static str {
+        "jena_stub"
+    }
+
+    fn execute_bindings_query(
+        &self,
+        _query: &str,
+        _events: &[RDFEvent],
+    ) -> Result<ExternalBindings, Box<dyn std::error::Error>> {
+        Err("Apache Jena adapter is not implemented yet".into())
+    }
+}
+
+fn rdf_event_to_quad(event: &RDFEvent) -> Result<Quad, Box<dyn std::error::Error>> {
+    let subject = NamedNode::new(event.subject.as_str())?;
+    let predicate = NamedNode::new(event.predicate.as_str())?;
+    let object = if event.object.starts_with("http://") || event.object.starts_with("https://") {
+        Term::NamedNode(NamedNode::new(event.object.as_str())?)
+    } else {
+        Term::Literal(event.object.as_str().into())
+    };
+    let graph = if event.graph.is_empty() {
+        GraphName::DefaultGraph
+    } else {
+        GraphName::NamedNode(NamedNode::new(event.graph.as_str())?)
+    };
+    Ok(Quad::new(subject, predicate, object, graph))
+}
diff --git a/src/paper_bench/harness.rs b/src/paper_bench/harness.rs
new file mode 100644
index 0000000..285f3d0
--- /dev/null
+++ b/src/paper_bench/harness.rs
@@ -0,0 +1,3301 @@
+use crate::{
+    api::janus_api::JanusApiError,
+    core::RDFEvent,
+    execution::HistoricalExecutor,
+    paper_bench::external::{ExternalBindings, ExternalHistoricalAdapter},
+    parsing::janusql_parser::JanusQLParser,
+    querying::oxigraph_adapter::OxigraphAdapter,
+    storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
+    stream::live_stream_processing::LiveStreamProcessing,
+};
+use clap::ValueEnum;
+use serde::Serialize;
+use sha2::{Digest, Sha256};
+use std::{
+    cmp::Ordering,
+    collections::{HashMap, HashSet},
+    env,
+    fs::{self, File},
+    io::Write,
+    path::{Path, PathBuf},
+    process::Command,
+    sync::{
+        atomic::{AtomicU64, Ordering as AtomicOrdering},
+        Arc,
+    },
+    time::{Duration, Instant, SystemTime, UNIX_EPOCH},
+};
+
+const BASELINE_NS: &str = "https://janus.rs/baseline#";
+const GRAPH_URI: &str = "http://example.org/citybench";
+const LIVE_STREAM_URI: &str = "http://example.org/live";
+const TRAFFIC_PREDICATE: &str = "http://example.org/trafficFlow";
+const BASELINE_PREDICATE: &str = "http://example.org/baselineFlow";
+
+static CONFIG_COUNTER: AtomicU64 = AtomicU64::new(0);
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Serialize, ValueEnum)]
+#[serde(rename_all = "snake_case")]
+pub enum ExecutionMode {
+    Cold,
+    Warm,
+}
+
+impl ExecutionMode {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Cold => "cold",
+            Self::Warm => "warm",
+        }
+    }
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Serialize, ValueEnum)]
+#[serde(rename_all = "kebab-case")]
+pub enum TimeMode {
+    Virtual,
+    WallClock,
+}
+
+impl TimeMode {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Virtual => "virtual",
+            Self::WallClock => "wall-clock",
+        }
+    }
+
+    pub fn uses_virtual_event_time(self) -> bool {
+        matches!(self, Self::Virtual)
+    }
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq)]
+pub enum CoordinationSystem {
+    JanusUnified,
+    DecomposedOxigraph,
+}
+
+impl CoordinationSystem {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::JanusUnified => "janus_unified",
+            Self::DecomposedOxigraph => {
+                "Oxigraph historical + Janus live window processor + external join"
+            }
+        }
+    }
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct ReproMetadata {
+    pub git_commit_sha: String,
+    pub branch: String,
+    pub rustc_version: String,
+    pub os: String,
+    pub cpu_model: String,
+    pub ram_bytes: Option<u64>,
+    pub benchmark_command: String,
+    pub timestamp_unix_ms: u64,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct CoordinationRow {
+    pub system: String,
+    pub mode: String,
+    pub is_warmup: bool,
+    pub run_index: usize,
+    pub historical_events: usize,
+    pub live_events: usize,
+    pub client_start: u64,
+    pub query_registered: u64,
+    pub historical_start: u64,
+    pub historical_done: u64,
+    pub live_ready: u64,
+    pub first_event_published: u64,
+    pub first_result_engine: u64,
+    pub first_result_client: u64,
+    pub e2e_latency_ms: f64,
+    pub estimated_useful_engine_work_ms: f64,
+    pub estimated_coordination_overhead_ms: f64,
+    pub historical_intermediate_bytes: usize,
+    pub live_intermediate_bytes: usize,
+    pub estimated_external_transfer_bytes: usize,
+    pub final_result_bytes: usize,
+    pub components: usize,
+    pub process_boundaries: usize,
+    pub serialization_steps: usize,
+    pub result_count: usize,
+    pub historical_input_hash: String,
+    pub live_input_hash: String,
+    pub result_hash: String,
+    pub equivalent_to_baseline: Option<bool>,
+    pub metadata: ReproMetadata,
+
+    // Explicit H1.1 Live-Stream and Correctness fields
+    pub live_events_published: usize,
+    pub live_events_processed: usize,
+    pub live_window_size: usize,
+    pub live_window_slide: usize,
+    pub live_query_registered_at: u64,
+    pub live_first_event_at: u64,
+    pub live_first_window_result_at: u64,
+    pub live_stream_processing_latency_ms: f64,
+    pub external_join_latency_ms: f64,
+    pub first_hybrid_result_latency_ms: f64,
+    pub historical_result_count: usize,
+    pub historical_result_hash: String,
+    pub live_result_count: usize,
+    pub live_result_hash: Option<String>,
+    pub hybrid_result_count: usize,
+    pub hybrid_result_hash: String,
+    pub historical_equivalent_to_baseline: Option<bool>,
+    pub hybrid_equivalent_to_baseline: Option<bool>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct CoordinationSummaryRow {
+    pub system: String,
+    pub mode: String,
+    pub runs: usize,
+    pub components: usize,
+    pub process_boundaries: usize,
+    pub serialization_steps: usize,
+    pub p50_e2e_latency_ms: f64,
+    pub p95_e2e_latency_ms: f64,
+    pub avg_useful_engine_work_ms: f64,
+    pub avg_coordination_overhead_ms: f64,
+    pub avg_external_transfer_bytes: f64,
+    pub avg_final_result_bytes: f64,
+    pub avg_result_count: f64,
+
+    // Explicit H1.1 live-stream and equivalence rate fields
+    pub avg_live_events_published: f64,
+    pub avg_live_events_processed: f64,
+    pub avg_live_stream_processing_latency_ms: f64,
+    pub avg_external_join_latency_ms: f64,
+    pub avg_first_hybrid_result_latency_ms: f64,
+    pub avg_historical_result_count: f64,
+    pub avg_live_result_count: f64,
+    pub avg_hybrid_result_count: f64,
+    pub historical_equivalence_rate: f64,
+    pub hybrid_equivalence_rate: f64,
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Hash, Serialize, ValueEnum)]
+#[serde(rename_all = "snake_case")]
+pub enum ScalingQueryType {
+    PointLookup,
+    FixedWindow,
+    ProportionalRange10,
+    ProportionalRange50,
+    FullRange,
+    HybridBaselineLookup,
+}
+
+impl ScalingQueryType {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::PointLookup => "point_lookup",
+            Self::FixedWindow => "fixed_window",
+            Self::ProportionalRange10 => "proportional_range_10",
+            Self::ProportionalRange50 => "proportional_range_50",
+            Self::FullRange => "full_range",
+            Self::HybridBaselineLookup => "hybrid_baseline_lookup",
+        }
+    }
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct ScalingRow {
+    pub dataset_size_quads: usize,
+    pub query_type: String,
+    pub mode: String,
+    pub is_warmup: bool,
+    pub run_index: usize,
+    pub logical_quads_scanned: usize,
+    pub selectivity: f64,
+    pub result_count: usize,
+    pub result_hash: String,
+    pub latency_ms: f64,
+    pub p50_latency_ms: f64,
+    pub p95_latency_ms: f64,
+    pub throughput_quads_per_sec: f64,
+    pub peak_rss_mb: Option<f64>,
+    pub metadata: ReproMetadata,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct ScalingSummaryRow {
+    pub dataset_size_quads: usize,
+    pub query_type: String,
+    pub mode: String,
+    pub runs: usize,
+    pub logical_quads_scanned: usize,
+    pub selectivity: f64,
+    pub result_count: usize,
+    pub p50_latency_ms: f64,
+    pub p95_latency_ms: f64,
+    pub avg_latency_ms: f64,
+    pub avg_throughput_quads_per_sec: f64,
+    pub max_peak_rss_mb: Option<f64>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct ScalingFitRow {
+    pub query_type: String,
+    pub mode: String,
+    pub slope_ms_per_100k_quads: f64,
+    pub intercept_ms: f64,
+    pub r_squared: f64,
+    pub number_of_points: usize,
+}
+
+#[derive(Clone)]
+pub struct DatasetSpec {
+    pub size_quads: usize,
+    pub start_ts: u64,
+    pub end_ts: u64,
+    pub point_ts: u64,
+    pub point_subject: String,
+    pub fixed_start: u64,
+    pub fixed_end: u64,
+    pub proportional_10_end: u64,
+    pub proportional_50_end: u64,
+}
+
+#[derive(Clone)]
+pub struct HistoricalDataset {
+    pub storage: Arc<StreamingSegmentedStorage>,
+    pub spec: DatasetSpec,
+}
+
+#[derive(Clone)]
+pub struct CoordinationWorkload {
+    pub historical_storage: Arc<StreamingSegmentedStorage>,
+    pub historical_rdf_events: Vec<RDFEvent>,
+    pub live_events: Vec<RDFEvent>,
+    pub historical_start_ts: u64,
+    pub historical_end_ts: u64,
+    pub historical_sparql_query: String,
+    pub hybrid_query: String,
+}
+
+#[derive(Clone, Debug, Serialize)]
+struct JoinTraceRow {
+    historical_join_key: Option<String>,
+    live_join_key: Option<String>,
+    accepted: bool,
+    rejection_reason: Option<String>,
+    historical_row: Option<Vec<(String, String)>>,
+    live_row: Vec<(String, String)>,
+    joined_row: Option<Vec<(String, String)>>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+struct EquivalenceReport {
+    system_pair: String,
+    run_index: usize,
+    mode: String,
+    historical_input_hash: String,
+    live_input_hash: String,
+    janus_result_count: usize,
+    decomposed_result_count: usize,
+    janus_result_hash: String,
+    decomposed_result_hash: String,
+    equivalent: bool,
+    historical_inputs_semantically_equal: bool,
+    live_inputs_semantically_equal: bool,
+    notes: Vec<String>,
+}
+
+pub struct CoordinationPair {
+    pub unified: CoordinationRow,
+    pub decomposed: CoordinationRow,
+}
+
+pub struct CoordinationRunConfig<'a> {
+    pub mode: ExecutionMode,
+    pub run_index: usize,
+    pub is_warmup: bool,
+    pub historical_events: usize,
+    pub live_events: usize,
+    pub metadata: &'a ReproMetadata,
+    pub adapter: &'a dyn ExternalHistoricalAdapter,
+    pub warm_workload: Option<&'a CoordinationWorkload>,
+    pub debug_output_dir: Option<&'a Path>,
+}
+
+pub struct ScalingRunConfig<'a> {
+    pub mode: ExecutionMode,
+    pub dataset_size_quads: usize,
+    pub query_type: ScalingQueryType,
+    pub metadata: &'a ReproMetadata,
+    pub run_index: usize,
+    pub is_warmup: bool,
+    pub warm_dataset: Option<&'a HistoricalDataset>,
+    pub output_dir: &'a Path,
+}
+
+pub fn collect_repro_metadata() -> ReproMetadata {
+    ReproMetadata {
+        git_commit_sha: capture_command("git", &["rev-parse", "HEAD"]),
+        branch: capture_command("git", &["branch", "--show-current"]),
+        rustc_version: capture_command("rustc", &["--version"]),
+        os: detect_os(),
+        cpu_model: detect_cpu_model(),
+        ram_bytes: detect_ram_bytes(),
+        benchmark_command: env::args().collect::<Vec<_>>().join(" "),
+        timestamp_unix_ms: now_ms(),
+    }
+}
+
+pub fn ensure_output_dir(base: &Path) -> std::io::Result<()> {
+    fs::create_dir_all(base)
+}
+
+pub fn write_jsonl<T: Serialize>(path: &Path, rows: &[T]) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    for row in rows {
+        serde_json::to_writer(&mut file, row)?;
+        writeln!(file)?;
+    }
+    Ok(())
+}
+
+pub fn write_coordination_summary_csv(
+    path: &Path,
+    rows: &[CoordinationSummaryRow],
+) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "system,mode,runs,components,process_boundaries,serialization_steps,p50_e2e_latency_ms,p95_e2e_latency_ms,avg_useful_engine_work_ms,avg_coordination_overhead_ms,avg_external_transfer_bytes,avg_final_result_bytes,avg_result_count,avg_live_events_published,avg_live_events_processed,avg_live_stream_processing_latency_ms,avg_external_join_latency_ms,avg_first_hybrid_result_latency_ms,avg_historical_result_count,avg_live_result_count,avg_hybrid_result_count,historical_equivalence_rate,hybrid_equivalence_rate"
+    )?;
+    for row in rows {
+        writeln!(
+            file,
+            "{},{},{},{},{},{},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3}",
+            row.system,
+            row.mode,
+            row.runs,
+            row.components,
+            row.process_boundaries,
+            row.serialization_steps,
+            row.p50_e2e_latency_ms,
+            row.p95_e2e_latency_ms,
+            row.avg_useful_engine_work_ms,
+            row.avg_coordination_overhead_ms,
+            row.avg_external_transfer_bytes,
+            row.avg_final_result_bytes,
+            row.avg_result_count,
+            row.avg_live_events_published,
+            row.avg_live_events_processed,
+            row.avg_live_stream_processing_latency_ms,
+            row.avg_external_join_latency_ms,
+            row.avg_first_hybrid_result_latency_ms,
+            row.avg_historical_result_count,
+            row.avg_live_result_count,
+            row.avg_hybrid_result_count,
+            row.historical_equivalence_rate,
+            row.hybrid_equivalence_rate
+        )?;
+    }
+    Ok(())
+}
+
+pub fn write_scaling_summary_csv(path: &Path, rows: &[ScalingSummaryRow]) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "dataset_size_quads,query_type,mode,runs,logical_quads_scanned,selectivity,result_count,p50_latency_ms,p95_latency_ms,avg_latency_ms,avg_throughput_quads_per_sec,max_peak_rss_mb"
+    )?;
+    for row in rows {
+        let peak_rss = row.max_peak_rss_mb.map_or_else(String::new, |value| format!("{value:.3}"));
+        writeln!(
+            file,
+            "{},{},{},{},{},{:.6},{},{:.3},{:.3},{:.3},{:.3},{}",
+            row.dataset_size_quads,
+            row.query_type,
+            row.mode,
+            row.runs,
+            row.logical_quads_scanned,
+            row.selectivity,
+            row.result_count,
+            row.p50_latency_ms,
+            row.p95_latency_ms,
+            row.avg_latency_ms,
+            row.avg_throughput_quads_per_sec,
+            peak_rss
+        )?;
+    }
+    Ok(())
+}
+
+pub fn write_scaling_fit_csv(path: &Path, rows: &[ScalingFitRow]) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "query_type,mode,slope_ms_per_100k_quads,intercept_ms,r_squared,number_of_points"
+    )?;
+    for row in rows {
+        writeln!(
+            file,
+            "{},{},{:.6},{:.6},{:.6},{}",
+            row.query_type,
+            row.mode,
+            row.slope_ms_per_100k_quads,
+            row.intercept_ms,
+            row.r_squared,
+            row.number_of_points
+        )?;
+    }
+    Ok(())
+}
+
+pub fn summarize_coordination(rows: &[CoordinationRow]) -> Vec<CoordinationSummaryRow> {
+    let mut grouped = HashMap::<(String, String), Vec<&CoordinationRow>>::new();
+    for row in rows {
+        grouped.entry((row.system.clone(), row.mode.clone())).or_default().push(row);
+    }
+
+    let mut summary = grouped
+        .into_iter()
+        .map(|((system, mode), items)| {
+            let runs = items.len();
+            let historical_equiv_count = items
+                .iter()
+                .filter(|row| row.historical_equivalent_to_baseline == Some(true))
+                .count();
+            let hybrid_equiv_count = items
+                .iter()
+                .filter(|row| row.hybrid_equivalent_to_baseline == Some(true))
+                .count();
+
+            CoordinationSummaryRow {
+                system,
+                mode,
+                runs,
+                components: items.first().map_or(0, |row| row.components),
+                process_boundaries: items.first().map_or(0, |row| row.process_boundaries),
+                serialization_steps: items.first().map_or(0, |row| row.serialization_steps),
+                p50_e2e_latency_ms: percentile(
+                    &items.iter().map(|row| row.e2e_latency_ms).collect::<Vec<_>>(),
+                    50.0,
+                ),
+                p95_e2e_latency_ms: percentile(
+                    &items.iter().map(|row| row.e2e_latency_ms).collect::<Vec<_>>(),
+                    95.0,
+                ),
+                avg_useful_engine_work_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.estimated_useful_engine_work_ms)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_coordination_overhead_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.estimated_coordination_overhead_ms)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_external_transfer_bytes: mean_usize(
+                    &items
+                        .iter()
+                        .map(|row| row.estimated_external_transfer_bytes)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_final_result_bytes: mean_usize(
+                    &items.iter().map(|row| row.final_result_bytes).collect::<Vec<_>>(),
+                ),
+                avg_result_count: mean_usize(
+                    &items.iter().map(|row| row.result_count).collect::<Vec<_>>(),
+                ),
+                avg_live_events_published: mean_usize(
+                    &items.iter().map(|row| row.live_events_published).collect::<Vec<_>>(),
+                ),
+                avg_live_events_processed: mean_usize(
+                    &items.iter().map(|row| row.live_events_processed).collect::<Vec<_>>(),
+                ),
+                avg_live_stream_processing_latency_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.live_stream_processing_latency_ms)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_external_join_latency_ms: mean(
+                    &items.iter().map(|row| row.external_join_latency_ms).collect::<Vec<_>>(),
+                ),
+                avg_first_hybrid_result_latency_ms: mean(
+                    &items.iter().map(|row| row.first_hybrid_result_latency_ms).collect::<Vec<_>>(),
+                ),
+                avg_historical_result_count: mean_usize(
+                    &items.iter().map(|row| row.historical_result_count).collect::<Vec<_>>(),
+                ),
+                avg_live_result_count: mean_usize(
+                    &items.iter().map(|row| row.live_result_count).collect::<Vec<_>>(),
+                ),
+                avg_hybrid_result_count: mean_usize(
+                    &items.iter().map(|row| row.hybrid_result_count).collect::<Vec<_>>(),
+                ),
+                historical_equivalence_rate: if runs > 0 {
+                    historical_equiv_count as f64 / runs as f64
+                } else {
+                    0.0
+                },
+                hybrid_equivalence_rate: if runs > 0 {
+                    hybrid_equiv_count as f64 / runs as f64
+                } else {
+                    0.0
+                },
+            }
+        })
+        .collect::<Vec<_>>();
+    summary.sort_by(|left, right| {
+        left.system.cmp(&right.system).then_with(|| left.mode.cmp(&right.mode))
+    });
+    summary
+}
+
+pub fn summarize_scaling(rows: &[ScalingRow]) -> Vec<ScalingSummaryRow> {
+    let mut grouped = HashMap::<(usize, String, String), Vec<&ScalingRow>>::new();
+    for row in rows {
+        grouped
+            .entry((row.dataset_size_quads, row.query_type.clone(), row.mode.clone()))
+            .or_default()
+            .push(row);
+    }
+
+    let mut summary = grouped
+        .into_iter()
+        .map(|((dataset_size_quads, query_type, mode), items)| ScalingSummaryRow {
+            dataset_size_quads,
+            query_type,
+            mode,
+            runs: items.len(),
+            logical_quads_scanned: items.first().map_or(0, |row| row.logical_quads_scanned),
+            selectivity: items.first().map_or(0.0, |row| row.selectivity),
+            result_count: items.first().map_or(0, |row| row.result_count),
+            p50_latency_ms: percentile(
+                &items.iter().map(|row| row.latency_ms).collect::<Vec<_>>(),
+                50.0,
+            ),
+            p95_latency_ms: percentile(
+                &items.iter().map(|row| row.latency_ms).collect::<Vec<_>>(),
+                95.0,
+            ),
+            avg_latency_ms: mean(&items.iter().map(|row| row.latency_ms).collect::<Vec<_>>()),
+            avg_throughput_quads_per_sec: mean(
+                &items.iter().map(|row| row.throughput_quads_per_sec).collect::<Vec<_>>(),
+            ),
+            max_peak_rss_mb: items
+                .iter()
+                .filter_map(|row| row.peak_rss_mb)
+                .max_by(|left, right| left.partial_cmp(right).unwrap_or(Ordering::Equal)),
+        })
+        .collect::<Vec<_>>();
+    summary.sort_by(|left, right| {
+        left.dataset_size_quads
+            .cmp(&right.dataset_size_quads)
+            .then_with(|| left.query_type.cmp(&right.query_type))
+            .then_with(|| left.mode.cmp(&right.mode))
+    });
+    summary
+}
+
+pub fn summarize_scaling_fit(rows: &[ScalingRow]) -> Vec<ScalingFitRow> {
+    let mut grouped = HashMap::<(String, String), Vec<&ScalingRow>>::new();
+    for row in rows {
+        grouped.entry((row.query_type.clone(), row.mode.clone())).or_default().push(row);
+    }
+
+    let mut fit_rows = grouped
+        .into_iter()
+        .map(|((query_type, mode), items)| {
+            let mut points = HashMap::<usize, Vec<f64>>::new();
+            for row in items {
+                points.entry(row.dataset_size_quads).or_default().push(row.latency_ms);
+            }
+            let mut sorted_points = points
+                .into_iter()
+                .map(|(size, values)| (size as f64, mean(&values)))
+                .collect::<Vec<_>>();
+            sorted_points
+                .sort_by(|left, right| left.0.partial_cmp(&right.0).unwrap_or(Ordering::Equal));
+            linear_fit_row(&query_type, &mode, &sorted_points)
+        })
+        .collect::<Vec<_>>();
+    fit_rows.sort_by(|left, right| {
+        left.query_type.cmp(&right.query_type).then_with(|| left.mode.cmp(&right.mode))
+    });
+    fit_rows
+}
+
+pub fn fill_scaling_percentiles(rows: &mut [ScalingRow]) {
+    let mut grouped = HashMap::<(usize, String, String), Vec<usize>>::new();
+    for (index, row) in rows.iter().enumerate() {
+        grouped
+            .entry((row.dataset_size_quads, row.query_type.clone(), row.mode.clone()))
+            .or_default()
+            .push(index);
+    }
+
+    for indexes in grouped.values() {
+        let latencies = indexes.iter().map(|index| rows[*index].latency_ms).collect::<Vec<_>>();
+        let p50 = percentile(&latencies, 50.0);
+        let p95 = percentile(&latencies, 95.0);
+        for index in indexes {
+            rows[*index].p50_latency_ms = p50;
+            rows[*index].p95_latency_ms = p95;
+        }
+    }
+}
+
+pub fn generate_citybench_dataset(
+    size_quads: usize,
+    output_dir: &Path,
+) -> Result<HistoricalDataset, Box<dyn std::error::Error>> {
+    let logs_dir = output_dir.join("logs");
+    fs::create_dir_all(&logs_dir)?;
+    let log_path = logs_dir.join(format!("citybench_{size_quads}.nq"));
+
+    let mut log_file = File::create(&log_path)?;
+    let storage = Arc::new(StreamingSegmentedStorage::new(unique_config("paper_scaling"))?);
+    let start_ts = 1_720_000_000_000;
+    let fixed_window = 1_000usize.min(size_quads.max(1));
+    let range_10 = (size_quads / 10).max(1);
+    let range_50 = (size_quads / 2).max(1);
+    let midpoint = size_quads / 2;
+    let point_ts = start_ts + midpoint as u64;
+    let point_subject = format!("http://example.org/junction/{}", midpoint % 256);
+
+    for index in 0..size_quads {
+        let event = citybench_event(start_ts + index as u64, index);
+        writeln!(
+            log_file,
+            "{} <{}> <{}> \"{}\" <{}> .",
+            event.timestamp, event.subject, event.predicate, event.object, event.graph
+        )?;
+        storage.write_rdf_event(event)?;
+    }
+    storage.flush()?;
+
+    Ok(HistoricalDataset {
+        storage,
+        spec: DatasetSpec {
+            size_quads,
+            start_ts,
+            end_ts: start_ts + size_quads.saturating_sub(1) as u64,
+            point_ts,
+            point_subject,
+            fixed_start: start_ts + midpoint.saturating_sub(fixed_window / 2) as u64,
+            fixed_end: start_ts
+                + midpoint.saturating_sub(fixed_window / 2) as u64
+                + fixed_window as u64,
+            proportional_10_end: start_ts + range_10 as u64,
+            proportional_50_end: start_ts + range_50 as u64,
+        },
+    })
+}
+
+pub fn prepare_coordination_workload(
+    historical_events: usize,
+    live_events: usize,
+) -> Result<CoordinationWorkload, Box<dyn std::error::Error>> {
+    let historical_start_ts = 1_800_000_000_000;
+    let historical_storage = build_historical_storage(historical_events, historical_start_ts)?;
+    let historical_rdf_events = historical_storage.query_rdf(
+        historical_start_ts,
+        historical_start_ts + historical_events.saturating_sub(1) as u64,
+    )?;
+    Ok(CoordinationWorkload {
+        historical_storage,
+        historical_rdf_events,
+        live_events: build_live_events(live_events, 1_900_000_000_000),
+        historical_start_ts,
+        historical_end_ts: historical_start_ts + historical_events.saturating_sub(1) as u64,
+        historical_sparql_query: historical_baseline_sparql_query()?,
+        hybrid_query: hybrid_query(
+            historical_start_ts,
+            historical_start_ts + historical_events.saturating_sub(1) as u64,
+        ),
+    })
+}
+
+pub fn run_coordination_pair(
+    config: CoordinationRunConfig<'_>,
+) -> Result<CoordinationPair, Box<dyn std::error::Error>> {
+    let unified = run_coordination_system(CoordinationSystem::JanusUnified, &config)?;
+    let decomposed = run_coordination_system(CoordinationSystem::DecomposedOxigraph, &config)?;
+
+    let historical_equivalent = unified.historical_result_hash == decomposed.historical_result_hash;
+    let hybrid_equivalent = unified.hybrid_result_hash == decomposed.hybrid_result_hash
+        && unified.hybrid_result_count == decomposed.hybrid_result_count;
+
+    let mut unified = unified;
+    let mut decomposed = decomposed;
+
+    unified.historical_equivalent_to_baseline = Some(historical_equivalent);
+    unified.hybrid_equivalent_to_baseline = Some(hybrid_equivalent);
+    unified.equivalent_to_baseline = Some(hybrid_equivalent); // hybrid is primary equivalence target
+
+    decomposed.historical_equivalent_to_baseline = None;
+    decomposed.hybrid_equivalent_to_baseline = None;
+    decomposed.equivalent_to_baseline = None;
+
+    if let Some(debug_output_dir) = config.debug_output_dir {
+        write_h1_debug_artifacts(debug_output_dir, &unified, &decomposed, &config)?;
+    }
+
+    Ok(CoordinationPair { unified, decomposed })
+}
+
+fn run_coordination_system(
+    system: CoordinationSystem,
+    config: &CoordinationRunConfig<'_>,
+) -> Result<CoordinationRow, Box<dyn std::error::Error>> {
+    let owned_workload;
+    let workload = if config.mode == ExecutionMode::Warm {
+        config.warm_workload.ok_or("warm mode requires prepared workload")?
+    } else {
+        owned_workload =
+            prepare_coordination_workload(config.historical_events, config.live_events)?;
+        &owned_workload
+    };
+
+    let client_start = now_ms();
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&workload.hybrid_query)?;
+    let query_registered = now_ms();
+
+    let historical_start = now_ms();
+    let executor =
+        HistoricalExecutor::new(Arc::clone(&workload.historical_storage), OxigraphAdapter::new());
+    let baseline_bindings = executor.execute_fixed_window(
+        parsed.historical_windows.first().ok_or("missing historical window")?,
+        &workload.historical_sparql_query,
+    )?;
+    let historical_done = now_ms();
+
+    let live_events_published = workload.live_events.len();
+    let live_events_processed = workload.live_events.len();
+    let live_window_size = 10000;
+    let live_window_slide = 1000;
+    let live_first_event_at = workload.live_events.first().map(|e| e.timestamp).unwrap_or(0);
+
+    match system {
+        CoordinationSystem::JanusUnified => {
+            let mut processor = LiveStreamProcessing::new(parsed.rspql_query.clone())?;
+            processor.register_stream(LIVE_STREAM_URI)?;
+            materialize_bindings_as_static_baseline(&mut processor, &baseline_bindings)?;
+            processor.start_processing()?;
+            let live_ready = now_ms();
+            publish_live_events(&processor, &workload.live_events)?;
+            let first_event_published = now_ms();
+            let live_collection = if workload.live_events.is_empty() {
+                LiveCollectionResult { first_result_engine_ms: now_ms(), all_rows: Vec::new() }
+            } else {
+                collect_live_results(
+                    &processor,
+                    Duration::from_millis(500),
+                    Duration::from_millis(10),
+                )?
+            };
+            let result_rows = live_collection.all_rows;
+            let first_result_engine = live_collection.first_result_engine_ms;
+            let first_result_client = now_ms();
+
+            let estimated_useful_engine_work_ms = (historical_done - historical_start) as f64
+                + (first_result_engine - first_event_published) as f64;
+            let e2e_latency_ms = (first_result_client - client_start) as f64;
+
+            let live_stream_processing_latency_ms =
+                (first_result_engine as f64 - first_event_published as f64).max(0.0);
+            let external_join_latency_ms = 0.0;
+            let first_hybrid_result_latency_ms = e2e_latency_ms;
+
+            let historical_result_count = baseline_bindings.len();
+            let historical_result_hash = canonical_result_hash(&baseline_bindings)?;
+            let live_result_count = 0;
+            let live_result_hash = None;
+            let hybrid_result_count = result_rows.len();
+            let hybrid_result_hash = canonical_result_hash(&result_rows)?;
+
+            Ok(CoordinationRow {
+                system: system.as_str().to_string(),
+                mode: config.mode.as_str().to_string(),
+                is_warmup: config.is_warmup,
+                run_index: config.run_index,
+                historical_events: config.historical_events,
+                live_events: config.live_events,
+                client_start,
+                query_registered,
+                historical_start,
+                historical_done,
+                live_ready,
+                first_event_published,
+                first_result_engine,
+                first_result_client,
+                e2e_latency_ms,
+                estimated_useful_engine_work_ms,
+                estimated_coordination_overhead_ms: (e2e_latency_ms
+                    - estimated_useful_engine_work_ms)
+                    .max(0.0),
+                historical_intermediate_bytes: serde_json::to_vec(&baseline_bindings)?.len(),
+                live_intermediate_bytes: serde_json::to_vec(&event_payloads(
+                    &workload.live_events,
+                ))?
+                .len(),
+                estimated_external_transfer_bytes: 0,
+                final_result_bytes: serde_json::to_vec(&result_rows)?.len(),
+                components: 1,
+                process_boundaries: 0,
+                serialization_steps: 1,
+                result_count: result_rows.len(),
+                historical_input_hash: historical_input_hash(&workload.historical_rdf_events)?,
+                live_input_hash: live_input_hash(&workload.live_events)?,
+                result_hash: canonical_result_hash(&result_rows)?,
+                equivalent_to_baseline: None,
+                metadata: config.metadata.clone(),
+
+                live_events_published,
+                live_events_processed,
+                live_window_size,
+                live_window_slide,
+                live_query_registered_at: query_registered,
+                live_first_event_at,
+                live_first_window_result_at: first_result_engine,
+                live_stream_processing_latency_ms,
+                external_join_latency_ms,
+                first_hybrid_result_latency_ms,
+                historical_result_count,
+                historical_result_hash,
+                live_result_count,
+                live_result_hash,
+                hybrid_result_count,
+                hybrid_result_hash,
+                historical_equivalent_to_baseline: None,
+                hybrid_equivalent_to_baseline: None,
+            })
+        }
+        CoordinationSystem::DecomposedOxigraph => {
+            let external_bindings = config.adapter.execute_bindings_query(
+                &workload.historical_sparql_query,
+                &workload.historical_rdf_events,
+            )?;
+            let materialized_baseline_rows =
+                materialized_baseline_rows_from_bindings(&external_bindings, "baselineFlow");
+            let historical_done = now_ms();
+            let mut processor = LiveStreamProcessing::new(live_only_rspql())?;
+            processor.register_stream(LIVE_STREAM_URI)?;
+            processor.start_processing()?;
+            let live_ready = now_ms();
+            publish_live_events(&processor, &workload.live_events)?;
+            let first_event_published = now_ms();
+            let live_collection = if workload.live_events.is_empty() {
+                LiveCollectionResult { first_result_engine_ms: now_ms(), all_rows: Vec::new() }
+            } else {
+                collect_live_results(
+                    &processor,
+                    Duration::from_millis(500),
+                    Duration::from_millis(10),
+                )?
+            };
+            let live_rows = live_collection.all_rows;
+            let joined_rows = join_live_with_baseline(&live_rows, &materialized_baseline_rows);
+            let first_result_engine = live_collection.first_result_engine_ms;
+            let first_result_client = now_ms();
+
+            let estimated_useful_engine_work_ms = (historical_done - historical_start) as f64
+                + (first_result_engine - first_event_published) as f64;
+            let e2e_latency_ms = (first_result_client - client_start) as f64;
+
+            let live_stream_processing_latency_ms =
+                (first_result_engine as f64 - first_event_published as f64).max(0.0);
+            let external_join_latency_ms =
+                (first_result_client as f64 - first_result_engine as f64).max(0.0);
+            let first_hybrid_result_latency_ms = e2e_latency_ms;
+
+            let historical_result_count = external_bindings.len();
+            let historical_result_hash = canonical_result_hash(&external_bindings)?;
+            let live_result_count = live_rows.len();
+            let live_result_hash = Some(canonical_result_hash(&live_rows)?);
+            let hybrid_result_count = joined_rows.len();
+            let hybrid_result_hash = canonical_result_hash(&joined_rows)?;
+
+            let historical_intermediate_bytes = serde_json::to_vec(&external_bindings)?.len();
+            let live_intermediate_bytes =
+                serde_json::to_vec(&event_payloads(&workload.live_events))?.len();
+            Ok(CoordinationRow {
+                system: system.as_str().to_string(),
+                mode: config.mode.as_str().to_string(),
+                is_warmup: config.is_warmup,
+                run_index: config.run_index,
+                historical_events: config.historical_events,
+                live_events: config.live_events,
+                client_start,
+                query_registered,
+                historical_start,
+                historical_done,
+                live_ready,
+                first_event_published,
+                first_result_engine,
+                first_result_client,
+                e2e_latency_ms,
+                estimated_useful_engine_work_ms,
+                estimated_coordination_overhead_ms: (e2e_latency_ms
+                    - estimated_useful_engine_work_ms)
+                    .max(0.0),
+                historical_intermediate_bytes,
+                live_intermediate_bytes,
+                estimated_external_transfer_bytes: historical_intermediate_bytes
+                    + live_intermediate_bytes,
+                final_result_bytes: serde_json::to_vec(&joined_rows)?.len(),
+                components: 4,
+                process_boundaries: 3,
+                serialization_steps: 4,
+                result_count: joined_rows.len(),
+                historical_input_hash: historical_input_hash(&workload.historical_rdf_events)?,
+                live_input_hash: live_input_hash(&workload.live_events)?,
+                result_hash: canonical_result_hash(&joined_rows)?,
+                equivalent_to_baseline: None,
+                metadata: config.metadata.clone(),
+
+                live_events_published,
+                live_events_processed,
+                live_window_size,
+                live_window_slide,
+                live_query_registered_at: query_registered,
+                live_first_event_at,
+                live_first_window_result_at: first_result_engine,
+                live_stream_processing_latency_ms,
+                external_join_latency_ms,
+                first_hybrid_result_latency_ms,
+                historical_result_count,
+                historical_result_hash,
+                live_result_count,
+                live_result_hash,
+                hybrid_result_count,
+                hybrid_result_hash,
+                historical_equivalent_to_baseline: None,
+                hybrid_equivalent_to_baseline: None,
+            })
+        }
+    }
+}
+
+pub fn run_scaling_query(
+    config: ScalingRunConfig<'_>,
+) -> Result<ScalingRow, Box<dyn std::error::Error>> {
+    let owned_dataset;
+    let dataset = if config.mode == ExecutionMode::Warm {
+        config.warm_dataset.ok_or("warm mode requires prepared dataset")?
+    } else {
+        owned_dataset = generate_citybench_dataset(config.dataset_size_quads, config.output_dir)?;
+        &owned_dataset
+    };
+
+    let started = Instant::now();
+    let query_result = match config.query_type {
+        ScalingQueryType::PointLookup => run_historical_query(
+            Arc::clone(&dataset.storage),
+            historical_lookup_query(
+                dataset.spec.point_ts,
+                dataset.spec.point_ts,
+                Some(&dataset.spec.point_subject),
+            ),
+        )?,
+        ScalingQueryType::FixedWindow => run_historical_query(
+            Arc::clone(&dataset.storage),
+            historical_lookup_query(dataset.spec.fixed_start, dataset.spec.fixed_end, None),
+        )?,
+        ScalingQueryType::ProportionalRange10 => run_historical_query(
+            Arc::clone(&dataset.storage),
+            historical_lookup_query(dataset.spec.start_ts, dataset.spec.proportional_10_end, None),
+        )?,
+        ScalingQueryType::ProportionalRange50 => run_historical_query(
+            Arc::clone(&dataset.storage),
+            historical_lookup_query(dataset.spec.start_ts, dataset.spec.proportional_50_end, None),
+        )?,
+        ScalingQueryType::FullRange => run_historical_query(
+            Arc::clone(&dataset.storage),
+            historical_lookup_query(dataset.spec.start_ts, dataset.spec.end_ts, None),
+        )?,
+        ScalingQueryType::HybridBaselineLookup => {
+            run_hybrid_baseline_lookup(Arc::clone(&dataset.storage), &dataset.spec)?
+        }
+    };
+
+    let latency_ms = started.elapsed().as_secs_f64() * 1_000.0;
+    let throughput_quads_per_sec = if latency_ms == 0.0 {
+        0.0
+    } else {
+        query_result.logical_quads_scanned as f64 / (latency_ms / 1_000.0)
+    };
+
+    Ok(ScalingRow {
+        dataset_size_quads: dataset.spec.size_quads,
+        query_type: config.query_type.as_str().to_string(),
+        mode: config.mode.as_str().to_string(),
+        is_warmup: config.is_warmup,
+        run_index: config.run_index,
+        logical_quads_scanned: query_result.logical_quads_scanned,
+        selectivity: if dataset.spec.size_quads == 0 {
+            0.0
+        } else {
+            query_result.result_rows.len() as f64 / dataset.spec.size_quads as f64
+        },
+        result_count: query_result.result_rows.len(),
+        result_hash: canonical_result_hash(&query_result.result_rows)?,
+        latency_ms,
+        p50_latency_ms: 0.0,
+        p95_latency_ms: 0.0,
+        throughput_quads_per_sec,
+        peak_rss_mb: current_rss_bytes().map(|bytes| bytes as f64 / (1024.0 * 1024.0)),
+        metadata: config.metadata.clone(),
+    })
+}
+
+struct QueryExecutionResult {
+    logical_quads_scanned: usize,
+    result_rows: Vec<HashMap<String, String>>,
+}
+
+struct LiveCollectionResult {
+    first_result_engine_ms: u64,
+    all_rows: Vec<HashMap<String, String>>,
+}
+
+fn run_historical_query(
+    storage: Arc<StreamingSegmentedStorage>,
+    query: String,
+) -> Result<QueryExecutionResult, Box<dyn std::error::Error>> {
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&query)?;
+    let window = parsed.historical_windows.first().ok_or("missing historical window")?;
+    let logical_quads_scanned = storage
+        .query(window.start.ok_or("missing start")?, window.end.ok_or("missing end")?)?
+        .len();
+    let executor = HistoricalExecutor::new(storage, OxigraphAdapter::new());
+    let result_rows = executor.execute_fixed_window(
+        window,
+        parsed.sparql_queries.first().ok_or("missing historical query")?,
+    )?;
+    Ok(QueryExecutionResult { logical_quads_scanned, result_rows })
+}
+
+fn run_hybrid_baseline_lookup(
+    storage: Arc<StreamingSegmentedStorage>,
+    dataset: &DatasetSpec,
+) -> Result<QueryExecutionResult, Box<dyn std::error::Error>> {
+    let query = format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+        PREFIX baseline: <{BASELINE_NS}>
+
+        REGISTER RStream <output> AS
+        SELECT ?sensor ?liveFlow ?baselineFlow
+        FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START {} END {}]
+        FROM NAMED WINDOW ex:live ON STREAM <{LIVE_STREAM_URI}> [RANGE 5000 STEP 1000]
+        USING BASELINE ex:hist AGGREGATE
+        WHERE {{
+            WINDOW ex:hist {{
+                ?sensor ex:trafficFlow ?baselineFlow .
+            }}
+            WINDOW ex:live {{
+                ?sensor ex:trafficFlow ?liveFlow .
+            }}
+            ?sensor baseline:baselineFlow ?baselineFlow .
+        }}
+        "#,
+        dataset.start_ts, dataset.end_ts
+    );
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&query)?;
+    let window = parsed.historical_windows.first().ok_or("missing historical window")?;
+    let logical_quads_scanned = storage.query(dataset.start_ts, dataset.end_ts)?.len();
+    let executor = HistoricalExecutor::new(Arc::clone(&storage), OxigraphAdapter::new());
+    let bindings = executor.execute_fixed_window(
+        window,
+        parsed.sparql_queries.first().ok_or("missing historical query")?,
+    )?;
+    let mut processor = LiveStreamProcessing::new(parsed.rspql_query.clone())?;
+    processor.register_stream(LIVE_STREAM_URI)?;
+    materialize_bindings_as_static_baseline(&mut processor, &bindings)?;
+    processor.start_processing()?;
+    processor.add_event(
+        LIVE_STREAM_URI,
+        RDFEvent::new(
+            dataset.end_ts + 1,
+            &dataset.point_subject,
+            TRAFFIC_PREDICATE,
+            "77",
+            GRAPH_URI,
+        ),
+    )?;
+    processor.close_stream(
+        LIVE_STREAM_URI,
+        i64::try_from(dataset.end_ts + 10_000).unwrap_or(i64::MAX),
+    )?;
+    let result_rows =
+        collect_live_results(&processor, Duration::from_secs(10), Duration::from_millis(10))?
+            .all_rows;
+    Ok(QueryExecutionResult { logical_quads_scanned, result_rows })
+}
+
+fn materialize_bindings_as_static_baseline(
+    processor: &mut LiveStreamProcessing,
+    bindings: &[HashMap<String, String>],
+) -> Result<(), JanusApiError> {
+    for (subject, predicate, object) in baseline_statements_from_bindings(bindings) {
+        processor
+            .add_static_data(RDFEvent::new(0, &subject, &predicate, &object, ""))
+            .map_err(|err| {
+                JanusApiError::LiveProcessingError(format!(
+                    "Failed to materialize baseline statement '{} {} {}': {}",
+                    subject, predicate, object, err
+                ))
+            })?;
+    }
+    Ok(())
+}
+
+fn baseline_statements_from_bindings(
+    bindings: &[HashMap<String, String>],
+) -> Vec<(String, String, String)> {
+    let mut accumulator = HashMap::<(String, String), BaselineAccumulator>::new();
+    for binding in bindings {
+        let Some(subject) = binding
+            .get("sensor")
+            .or_else(|| binding.get("s"))
+            .map(|value| normalize_binding_term(value))
+        else {
+            continue;
+        };
+
+        let mut keys = binding.keys().cloned().collect::<Vec<_>>();
+        keys.sort_unstable();
+        for key in keys {
+            if key == "sensor" || key == "s" {
+                continue;
+            }
+            let Some(value) = binding.get(&key).map(|raw| normalize_binding_term(raw)) else {
+                continue;
+            };
+            let entry = accumulator
+                .entry((subject.clone(), key))
+                .or_insert_with(BaselineAccumulator::new);
+            entry.last_value.clone_from(&value);
+            if let Ok(number) = value.parse::<f64>() {
+                entry.numeric_sum += number;
+                entry.numeric_count += 1;
+            } else {
+                entry.all_numeric = false;
+            }
+        }
+    }
+
+    let mut rows = accumulator.into_iter().collect::<Vec<_>>();
+    rows.sort_by(|((left_subject, left_var), _), ((right_subject, right_var), _)| {
+        left_subject.cmp(right_subject).then_with(|| left_var.cmp(right_var))
+    });
+    rows.into_iter()
+        .map(|((subject, variable), acc)| {
+            let object = if acc.all_numeric && acc.numeric_count > 0 {
+                (acc.numeric_sum / acc.numeric_count as f64).to_string()
+            } else {
+                acc.last_value
+            };
+            (subject, format!("{BASELINE_NS}{variable}"), object)
+        })
+        .collect()
+}
+
+fn materialized_baseline_rows_from_bindings(
+    bindings: &[HashMap<String, String>],
+    baseline_variable: &str,
+) -> Vec<HashMap<String, String>> {
+    baseline_statements_from_bindings(bindings)
+        .into_iter()
+        .filter_map(|(subject, predicate, object)| {
+            predicate
+                .strip_prefix(BASELINE_NS)
+                .map(|variable_name| (subject, variable_name.to_string(), object))
+        })
+        .filter(|(_, variable_name, _)| variable_name == baseline_variable)
+        .map(|(subject, variable_name, object)| {
+            HashMap::from([("sensor".to_string(), subject), (variable_name, object)])
+        })
+        .collect()
+}
+
+fn join_live_with_baseline(
+    live_rows: &[HashMap<String, String>],
+    baseline_rows: &[HashMap<String, String>],
+) -> Vec<HashMap<String, String>> {
+    join_live_with_baseline_detailed(live_rows, baseline_rows).0
+}
+
+fn join_live_with_baseline_detailed(
+    live_rows: &[HashMap<String, String>],
+    baseline_rows: &[HashMap<String, String>],
+) -> (Vec<HashMap<String, String>>, Vec<JoinTraceRow>) {
+    let mut baseline_by_subject = HashMap::<String, HashMap<String, String>>::new();
+    for row in baseline_rows {
+        let Some(subject) = row
+            .get("sensor")
+            .or_else(|| row.get("s"))
+            .map(|value| normalize_binding_term(value))
+        else {
+            continue;
+        };
+        baseline_by_subject.insert(subject, row.clone());
+    }
+
+    let mut joined = Vec::new();
+    let mut trace = Vec::new();
+    for live_row in live_rows {
+        let Some(subject) = live_row
+            .get("sensor")
+            .or_else(|| live_row.get("s"))
+            .map(|value| normalize_binding_term(value))
+        else {
+            trace.push(JoinTraceRow {
+                historical_join_key: None,
+                live_join_key: None,
+                accepted: false,
+                rejection_reason: Some("missing_live_join_key".to_string()),
+                historical_row: None,
+                live_row: canonicalize_row(live_row),
+                joined_row: None,
+            });
+            continue;
+        };
+        if let Some(baseline_row) = baseline_by_subject.get(&subject) {
+            let mut merged = baseline_row.clone();
+            for (key, value) in live_row {
+                merged.insert(key.clone(), value.clone());
+            }
+            trace.push(JoinTraceRow {
+                historical_join_key: Some(subject.clone()),
+                live_join_key: Some(subject),
+                accepted: true,
+                rejection_reason: None,
+                historical_row: Some(canonicalize_row(baseline_row)),
+                live_row: canonicalize_row(live_row),
+                joined_row: Some(canonicalize_row(&merged)),
+            });
+            joined.push(merged);
+        } else {
+            trace.push(JoinTraceRow {
+                historical_join_key: None,
+                live_join_key: Some(subject),
+                accepted: false,
+                rejection_reason: Some("no_historical_row_for_join_key".to_string()),
+                historical_row: None,
+                live_row: canonicalize_row(live_row),
+                joined_row: None,
+            });
+        }
+    }
+    (joined, trace)
+}
+
+fn build_historical_storage(
+    events: usize,
+    start_ts: u64,
+) -> Result<Arc<StreamingSegmentedStorage>, Box<dyn std::error::Error>> {
+    let storage = Arc::new(StreamingSegmentedStorage::new(unique_config("paper_h1"))?);
+    for index in 0..events {
+        let event = RDFEvent::new(
+            start_ts + index as u64,
+            &format!("http://example.org/junction/{}", index % 64),
+            BASELINE_PREDICATE,
+            &(40 + (index % 17)).to_string(),
+            GRAPH_URI,
+        );
+        storage.write_rdf_event(event)?;
+    }
+    storage.flush()?;
+    Ok(storage)
+}
+
+fn build_live_events(events: usize, start_ts: u64) -> Vec<RDFEvent> {
+    (0..events)
+        .map(|index| {
+            RDFEvent::new(
+                start_ts + index as u64,
+                &format!("http://example.org/junction/{}", index % 64),
+                TRAFFIC_PREDICATE,
+                &(70 + (index % 11)).to_string(),
+                GRAPH_URI,
+            )
+        })
+        .collect()
+}
+
+fn hybrid_query(start_ts: u64, end_ts: u64) -> String {
+    format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+        PREFIX baseline: <{BASELINE_NS}>
+
+        REGISTER RStream <output> AS
+        SELECT ?sensor ?liveFlow ?baselineFlow
+        FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START {start_ts} END {end_ts}]
+        FROM NAMED WINDOW ex:live ON STREAM <{LIVE_STREAM_URI}> [RANGE 10000 STEP 1000]
+        USING BASELINE ex:hist AGGREGATE
+        WHERE {{
+            WINDOW ex:hist {{
+                ?sensor ex:baselineFlow ?baselineFlow .
+            }}
+            WINDOW ex:live {{
+                ?sensor ex:trafficFlow ?liveFlow .
+            }}
+            ?sensor baseline:baselineFlow ?baselineFlow .
+        }}
+        "#
+    )
+}
+
+fn historical_baseline_sparql_query() -> Result<String, Box<dyn std::error::Error>> {
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+
+        SELECT ?sensor ?baselineFlow
+        FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START 1 END 2]
+        WHERE {{
+            WINDOW ex:hist {{
+                ?sensor ex:baselineFlow ?baselineFlow .
+            }}
+        }}
+        "#
+    ))?;
+    Ok(parsed
+        .sparql_queries
+        .first()
+        .cloned()
+        .ok_or("missing generated historical SPARQL query")?)
+}
+
+fn live_only_rspql() -> String {
+    format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+
+        REGISTER RStream <output> AS
+        SELECT ?sensor ?liveFlow
+        FROM NAMED WINDOW ex:live ON STREAM <{LIVE_STREAM_URI}> [RANGE 10000 STEP 1000]
+        WHERE {{
+            WINDOW ex:live {{
+                ?sensor ex:trafficFlow ?liveFlow .
+            }}
+        }}
+        "#
+    )
+}
+
+fn historical_lookup_query(start: u64, end: u64, subject_filter: Option<&str>) -> String {
+    let subject_clause = subject_filter
+        .map(|subject| format!("<{subject}> ex:trafficFlow ?trafficFlow ."))
+        .unwrap_or_else(|| "?sensor ex:trafficFlow ?trafficFlow .".to_string());
+    format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+
+        SELECT ?sensor ?trafficFlow
+        FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START {start} END {end}]
+        WHERE {{
+            WINDOW ex:hist {{
+                {subject_clause}
+            }}
+        }}
+        "#
+    )
+}
+
+fn publish_live_events(
+    processor: &LiveStreamProcessing,
+    live_events: &[RDFEvent],
+) -> Result<(), Box<dyn std::error::Error>> {
+    if live_events.is_empty() {
+        processor.close_stream(LIVE_STREAM_URI, 20_000_i64)?;
+        return Ok(());
+    }
+    let first = live_events.first().unwrap().clone();
+    processor.add_event(LIVE_STREAM_URI, first)?;
+    for event in live_events.iter().skip(1) {
+        processor.add_event(LIVE_STREAM_URI, event.clone())?;
+    }
+    let close_ts = live_events
+        .last()
+        .map_or(20_000_i64, |event| i64::try_from(event.timestamp).unwrap_or(i64::MAX) + 20_000);
+    processor.close_stream(LIVE_STREAM_URI, close_ts)?;
+    Ok(())
+}
+
+fn collect_live_results(
+    processor: &LiveStreamProcessing,
+    first_result_timeout: Duration,
+    idle_timeout: Duration,
+) -> Result<LiveCollectionResult, Box<dyn std::error::Error>> {
+    let deadline = Instant::now() + first_result_timeout;
+    loop {
+        if let Some(result) = processor.try_receive_result()? {
+            let first_result_engine_ms = now_ms();
+            let mut rows = vec![parse_rsprs_binding_string(&result.bindings)];
+            let mut idle_deadline = Instant::now() + idle_timeout;
+            loop {
+                if let Some(next_result) = processor.try_receive_result()? {
+                    rows.push(parse_rsprs_binding_string(&next_result.bindings));
+                    idle_deadline = Instant::now() + idle_timeout;
+                    continue;
+                }
+                if Instant::now() >= idle_deadline {
+                    return Ok(LiveCollectionResult { first_result_engine_ms, all_rows: rows });
+                }
+                std::thread::yield_now();
+            }
+        }
+        if Instant::now() >= deadline {
+            return Ok(LiveCollectionResult {
+                first_result_engine_ms: now_ms(),
+                all_rows: Vec::new(),
+            });
+        }
+        std::thread::yield_now();
+    }
+}
+
+fn event_payloads(events: &[RDFEvent]) -> Vec<(&str, &str, &str, &str, u64)> {
+    events
+        .iter()
+        .map(|event| {
+            (
+                event.subject.as_str(),
+                event.predicate.as_str(),
+                event.object.as_str(),
+                event.graph.as_str(),
+                event.timestamp,
+            )
+        })
+        .collect()
+}
+
+fn parse_rsprs_binding_string(binding_str: &str) -> HashMap<String, String> {
+    let mut result = HashMap::new();
+    let bindings_str = binding_str.trim_matches(|ch| ch == '{' || ch == '}').trim();
+    let parts = bindings_str.split(", Variable").collect::<Vec<_>>();
+
+    for (index, part) in parts.iter().enumerate() {
+        let binding = if index == 0 {
+            part.trim_start_matches("Variable")
+        } else {
+            part
+        };
+        let Some(name_start) = binding.find("name: \"") else {
+            continue;
+        };
+        let name_offset = name_start + 7;
+        let Some(name_end) = binding[name_offset..].find('"') else {
+            continue;
+        };
+        let variable = &binding[name_offset..name_offset + name_end];
+        let value = if binding.contains("TypedLiteral") {
+            extract_between(binding, "value: \"", "\"")
+        } else if binding.contains("NamedNode") {
+            extract_between(binding, "iri: \"", "\"")
+        } else if binding.contains("Literal(Literal(String(\"") {
+            extract_between(binding, "String(\"", "\")")
+        } else if binding.contains("Literal(Literal(") {
+            extract_between(binding, "Literal(Literal(", "))")
+        } else {
+            None
+        };
+        if let Some(value) = value {
+            result.insert(variable.to_string(), value);
+        }
+    }
+
+    result
+}
+
+fn extract_between(input: &str, start: &str, end: &str) -> Option<String> {
+    let start_index = input.find(start)? + start.len();
+    let end_index = input[start_index..].find(end)?;
+    Some(input[start_index..start_index + end_index].to_string())
+}
+
+fn citybench_event(timestamp: u64, index: usize) -> RDFEvent {
+    let junction = index % 256;
+    let flow = 20 + (index % 80);
+    RDFEvent::new(
+        timestamp,
+        &format!("http://example.org/junction/{junction}"),
+        TRAFFIC_PREDICATE,
+        &flow.to_string(),
+        GRAPH_URI,
+    )
+}
+
+fn canonical_result_hash(
+    rows: &[HashMap<String, String>],
+) -> Result<String, Box<dyn std::error::Error>> {
+    let mut canonical_rows = rows.iter().map(canonicalize_row).collect::<Vec<_>>();
+    canonical_rows.sort();
+    let payload = serde_json::to_vec(&canonical_rows)?;
+    let digest = Sha256::digest(payload);
+    Ok(format!("{digest:x}"))
+}
+
+fn canonicalize_row(row: &HashMap<String, String>) -> Vec<(String, String)> {
+    let mut entries = row
+        .iter()
+        .map(|(key, value)| (key.clone(), normalize_binding_term(value)))
+        .collect::<Vec<_>>();
+    entries.sort_by(|left, right| left.0.cmp(&right.0).then_with(|| left.1.cmp(&right.1)));
+    entries
+}
+
+fn linear_fit_row(query_type: &str, mode: &str, points: &[(f64, f64)]) -> ScalingFitRow {
+    if points.is_empty() {
+        return ScalingFitRow {
+            query_type: query_type.to_string(),
+            mode: mode.to_string(),
+            slope_ms_per_100k_quads: 0.0,
+            intercept_ms: 0.0,
+            r_squared: 0.0,
+            number_of_points: 0,
+        };
+    }
+
+    let n = points.len() as f64;
+    let mean_x = points.iter().map(|(x, _)| x).sum::<f64>() / n;
+    let mean_y = points.iter().map(|(_, y)| y).sum::<f64>() / n;
+    let numerator = points.iter().map(|(x, y)| (x - mean_x) * (y - mean_y)).sum::<f64>();
+    let denominator = points.iter().map(|(x, _)| (x - mean_x).powi(2)).sum::<f64>();
+    let slope = if denominator == 0.0 {
+        0.0
+    } else {
+        numerator / denominator
+    };
+    let intercept = mean_y - slope * mean_x;
+
+    let ss_tot = points.iter().map(|(_, y)| (y - mean_y).powi(2)).sum::<f64>();
+    let ss_res = points
+        .iter()
+        .map(|(x, y)| {
+            let predicted = intercept + slope * x;
+            (y - predicted).powi(2)
+        })
+        .sum::<f64>();
+    let r_squared = if ss_tot == 0.0 {
+        1.0
+    } else {
+        1.0 - (ss_res / ss_tot)
+    };
+
+    ScalingFitRow {
+        query_type: query_type.to_string(),
+        mode: mode.to_string(),
+        slope_ms_per_100k_quads: slope * 100_000.0,
+        intercept_ms: intercept,
+        r_squared,
+        number_of_points: points.len(),
+    }
+}
+
+fn percentile(values: &[f64], pct: f64) -> f64 {
+    if values.is_empty() {
+        return 0.0;
+    }
+    let mut sorted = values.to_vec();
+    sorted.sort_by(|left, right| left.partial_cmp(right).unwrap_or(Ordering::Equal));
+    let rank = ((pct / 100.0) * (sorted.len().saturating_sub(1) as f64)).round() as usize;
+    sorted[rank]
+}
+
+fn mean(values: &[f64]) -> f64 {
+    if values.is_empty() {
+        0.0
+    } else {
+        values.iter().sum::<f64>() / values.len() as f64
+    }
+}
+
+fn mean_usize(values: &[usize]) -> f64 {
+    if values.is_empty() {
+        0.0
+    } else {
+        values.iter().sum::<usize>() as f64 / values.len() as f64
+    }
+}
+
+fn now_ms() -> u64 {
+    SystemTime::now().duration_since(UNIX_EPOCH).unwrap_or_default().as_millis() as u64
+}
+
+fn unique_config(prefix: &str) -> StreamingConfig {
+    let counter = CONFIG_COUNTER.fetch_add(1, AtomicOrdering::Relaxed);
+    StreamingConfig {
+        segment_base_path: format!("/tmp/janus_{prefix}_{}_{}", now_ms(), counter),
+        max_batch_events: 1_000_000,
+        max_batch_age_seconds: 3600,
+        max_batch_bytes: 1_000_000_000,
+        sparse_interval: 64,
+        entries_per_index_block: 256,
+    }
+}
+
+fn capture_command(program: &str, args: &[&str]) -> String {
+    Command::new(program)
+        .args(args)
+        .output()
+        .ok()
+        .filter(|output| output.status.success())
+        .and_then(|output| String::from_utf8(output.stdout).ok())
+        .map(|value| value.trim().to_string())
+        .filter(|value| !value.is_empty())
+        .unwrap_or_else(|| "unknown".to_string())
+}
+
+fn detect_os() -> String {
+    format!("{} {}", env::consts::OS, capture_command("uname", &["-r"]))
+}
+
+fn detect_cpu_model() -> String {
+    #[cfg(target_os = "macos")]
+    {
+        let model = capture_command("sysctl", &["-n", "machdep.cpu.brand_string"]);
+        if model != "unknown" {
+            return model;
+        }
+    }
+    #[cfg(target_os = "linux")]
+    {
+        let model =
+            capture_command("sh", &["-c", "grep -m1 'model name' /proc/cpuinfo | cut -d: -f2-"]);
+        if model != "unknown" {
+            return model.trim().to_string();
+        }
+    }
+    "unknown".to_string()
+}
+
+fn detect_ram_bytes() -> Option<u64> {
+    #[cfg(target_os = "macos")]
+    {
+        return capture_command("sysctl", &["-n", "hw.memsize"]).parse::<u64>().ok();
+    }
+    #[cfg(target_os = "linux")]
+    {
+        return capture_command("sh", &["-c", "grep MemTotal /proc/meminfo | awk '{print $2}'"])
+            .parse::<u64>()
+            .ok()
+            .map(|kb| kb * 1024);
+    }
+    #[allow(unreachable_code)]
+    None
+}
+
+fn current_rss_bytes() -> Option<u64> {
+    capture_command("ps", &["-o", "rss=", "-p", &std::process::id().to_string()])
+        .parse::<u64>()
+        .ok()
+        .map(|kb| kb * 1024)
+}
+
+fn normalize_binding_term(raw: &str) -> String {
+    let trimmed = raw.trim();
+    if trimmed.starts_with("\\\"") && trimmed.contains("\\\"^^<") {
+        let without_prefix = &trimmed[2..];
+        if let Some(end) = without_prefix.find("\\\"^^<") {
+            return without_prefix[..end].to_string();
+        }
+    }
+    if trimmed.starts_with('"') && trimmed.contains("\"^^<") {
+        let without_prefix = &trimmed[1..];
+        if let Some(end) = without_prefix.find("\"^^<") {
+            return without_prefix[..end].to_string();
+        }
+    }
+    if trimmed.starts_with('<') && trimmed.ends_with('>') && trimmed.len() > 2 {
+        trimmed[1..trimmed.len() - 1].to_string()
+    } else if trimmed.starts_with('"') && trimmed.ends_with('"') && trimmed.len() > 2 {
+        trimmed[1..trimmed.len() - 1].to_string()
+    } else {
+        trimmed.to_string()
+    }
+}
+
+fn historical_input_hash(events: &[RDFEvent]) -> Result<String, Box<dyn std::error::Error>> {
+    let payload = serde_json::to_vec(&event_payloads(events))?;
+    Ok(format!("{:x}", Sha256::digest(payload)))
+}
+
+fn live_input_hash(events: &[RDFEvent]) -> Result<String, Box<dyn std::error::Error>> {
+    let payload = serde_json::to_vec(&event_payloads(events))?;
+    Ok(format!("{:x}", Sha256::digest(payload)))
+}
+
+fn event_payload_rows(events: &[RDFEvent]) -> Vec<HashMap<String, String>> {
+    events
+        .iter()
+        .map(|event| {
+            HashMap::from([
+                ("timestamp".to_string(), event.timestamp.to_string()),
+                ("subject".to_string(), event.subject.clone()),
+                ("predicate".to_string(), event.predicate.clone()),
+                ("object".to_string(), event.object.clone()),
+                ("graph".to_string(), event.graph.clone()),
+            ])
+        })
+        .collect()
+}
+
+fn canonical_result_rows(rows: &[HashMap<String, String>]) -> Vec<Vec<(String, String)>> {
+    let mut canonical = rows.iter().map(canonicalize_row).collect::<Vec<_>>();
+    canonical.sort();
+    canonical
+}
+
+fn write_trig_events(path: &Path, events: &[RDFEvent]) -> Result<(), Box<dyn std::error::Error>> {
+    let mut file = File::create(path)?;
+    let mut grouped = HashMap::<String, Vec<&RDFEvent>>::new();
+    for event in events {
+        grouped.entry(event.graph.clone()).or_default().push(event);
+    }
+    let mut graphs = grouped.into_iter().collect::<Vec<_>>();
+    graphs.sort_by(|left, right| left.0.cmp(&right.0));
+    for (graph, rows) in graphs {
+        writeln!(file, "<{}> {{", graph)?;
+        for event in rows {
+            writeln!(
+                file,
+                "  <{}> <{}> \"{}\" . # ts={}",
+                event.subject, event.predicate, event.object, event.timestamp
+            )?;
+        }
+        writeln!(file, "}}")?;
+    }
+    Ok(())
+}
+
+fn write_h1_debug_artifacts(
+    base_dir: &Path,
+    unified: &CoordinationRow,
+    decomposed: &CoordinationRow,
+    config: &CoordinationRunConfig<'_>,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let run_dir = base_dir.join("h1_equivalence_debug").join(format!(
+        "run_{:03}_{}",
+        config.run_index,
+        if config.is_warmup {
+            "warmup"
+        } else {
+            "measured"
+        }
+    ));
+    fs::create_dir_all(&run_dir)?;
+
+    let workload = config
+        .warm_workload
+        .ok_or("debug equivalence artifacts currently require warm workload")?;
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&workload.hybrid_query)?;
+    let executor =
+        HistoricalExecutor::new(Arc::clone(&workload.historical_storage), OxigraphAdapter::new());
+    let janus_historical_results = executor.execute_fixed_window(
+        parsed.historical_windows.first().ok_or("missing historical window")?,
+        &workload.historical_sparql_query,
+    )?;
+    let oxigraph_historical_results = config.adapter.execute_bindings_query(
+        &workload.historical_sparql_query,
+        &workload.historical_rdf_events,
+    )?;
+    let oxigraph_materialized_baseline =
+        materialized_baseline_rows_from_bindings(&oxigraph_historical_results, "baselineFlow");
+
+    let mut live_processor = LiveStreamProcessing::new(live_only_rspql())?;
+    live_processor.register_stream(LIVE_STREAM_URI)?;
+    live_processor.start_processing()?;
+    publish_live_events(&live_processor, &workload.live_events)?;
+    let live_rows =
+        collect_live_results(&live_processor, Duration::from_secs(10), Duration::from_millis(10))?
+            .all_rows;
+    let (decomposed_join_results, join_trace) =
+        join_live_with_baseline_detailed(&live_rows, &oxigraph_materialized_baseline);
+
+    let mut janus_processor = LiveStreamProcessing::new(parsed.rspql_query.clone())?;
+    janus_processor.register_stream(LIVE_STREAM_URI)?;
+    materialize_bindings_as_static_baseline(&mut janus_processor, &janus_historical_results)?;
+    janus_processor.start_processing()?;
+    publish_live_events(&janus_processor, &workload.live_events)?;
+    let janus_results =
+        collect_live_results(&janus_processor, Duration::from_secs(10), Duration::from_millis(10))?
+            .all_rows;
+
+    write_trig_events(
+        &run_dir.join("janus_input_historical.trig"),
+        &workload.historical_rdf_events,
+    )?;
+    write_trig_events(
+        &run_dir.join("oxigraph_input_historical.trig"),
+        &workload.historical_rdf_events,
+    )?;
+    write_jsonl(&run_dir.join("live_events.jsonl"), &event_payload_rows(&workload.live_events))?;
+    write_jsonl(&run_dir.join("janus_results.jsonl"), &janus_results)?;
+    write_jsonl(&run_dir.join("oxigraph_historical_results.jsonl"), &oxigraph_historical_results)?;
+    write_jsonl(
+        &run_dir.join("oxigraph_materialized_baseline.jsonl"),
+        &oxigraph_materialized_baseline,
+    )?;
+    write_jsonl(&run_dir.join("decomposed_join_results.jsonl"), &decomposed_join_results)?;
+    write_jsonl(
+        &run_dir.join("canonical_janus_results.jsonl"),
+        &canonical_result_rows(&janus_results),
+    )?;
+    write_jsonl(
+        &run_dir.join("canonical_decomposed_results.jsonl"),
+        &canonical_result_rows(&decomposed_join_results),
+    )?;
+    write_jsonl(&run_dir.join("join_trace.jsonl"), &join_trace)?;
+    fs::write(
+        run_dir.join("oxigraph_query.rq"),
+        format!("{}\n", workload.historical_sparql_query),
+    )?;
+
+    let report = EquivalenceReport {
+        system_pair: "janus_unified_vs_decomposed_oxigraph".to_string(),
+        run_index: config.run_index,
+        mode: config.mode.as_str().to_string(),
+        historical_input_hash: unified.historical_input_hash.clone(),
+        live_input_hash: unified.live_input_hash.clone(),
+        janus_result_count: unified.result_count,
+        decomposed_result_count: decomposed.result_count,
+        janus_result_hash: unified.result_hash.clone(),
+        decomposed_result_hash: decomposed.result_hash.clone(),
+        equivalent: unified.equivalent_to_baseline.unwrap_or(false),
+        historical_inputs_semantically_equal: unified.historical_input_hash
+            == decomposed.historical_input_hash,
+        live_inputs_semantically_equal: unified.live_input_hash == decomposed.live_input_hash,
+        notes: vec![
+            "Historical inputs are emitted from the same RDFEvent sequence for Janus and Oxigraph."
+                .to_string(),
+            "TriG comments preserve source timestamps for debug inspection.".to_string(),
+        ],
+    };
+    fs::write(run_dir.join("equivalence_report.json"), serde_json::to_vec_pretty(&report)?)?;
+    Ok(())
+}
+
+struct BaselineAccumulator {
+    last_value: String,
+    numeric_sum: f64,
+    numeric_count: usize,
+    all_numeric: bool,
+}
+
+impl BaselineAccumulator {
+    fn new() -> Self {
+        Self { last_value: String::new(), numeric_sum: 0.0, numeric_count: 0, all_numeric: true }
+    }
+}
+
+// =========================================================================
+// H1.2 Sustained Hybrid Window Execution Benchmark
+// =========================================================================
+
+#[derive(Clone, Debug, Serialize)]
+pub struct SustainedRow {
+    pub system: String,
+    pub mode: String,
+    pub time_mode: String,
+    pub is_warmup: bool,
+    pub run_index: usize,
+    pub historical_events: usize,
+    pub logical_live_duration_seconds: usize,
+    pub event_rate_hz: usize,
+    pub event_interval_ms: f64,
+    pub expected_wall_clock_duration_ms: u64,
+    pub events_published: usize,
+    pub events_processed: usize,
+    pub window_size_ms: usize,
+    pub window_slide_ms: usize,
+    pub expected_completed_windows: usize,
+    pub completed_windows_total: usize,
+    pub completed_windows_in_horizon: usize,
+    pub flush_windows: usize,
+    pub missed_windows: usize,
+    pub historical_start_at: u64,
+    pub historical_ready_at: u64,
+    pub live_start_at: u64,
+    pub first_live_event_at: u64,
+    pub first_live_window_ready_at: u64,
+    pub first_hybrid_result_at: u64,
+    pub historical_preparation_latency_ms: f64,
+    pub first_live_window_latency_ms: f64,
+    pub first_hybrid_result_latency_ms: f64,
+    pub first_hybrid_result_wall_clock_ms: f64,
+    pub readiness_gap_ms: f64,
+    pub hybrid_wait_after_inputs_ready_ms: f64,
+    pub p50_window_hybrid_latency_ms: f64,
+    pub p95_window_hybrid_latency_ms: f64,
+    pub window_result_wall_clock_offsets_ms: Vec<f64>,
+    pub p50_window_result_wall_clock_offset_ms: f64,
+    pub p95_window_result_wall_clock_offset_ms: f64,
+    pub external_join_latency_total_ms: f64,
+    pub external_join_latency_avg_ms: f64,
+    pub estimated_external_transfer_bytes_total: usize,
+    pub estimated_external_transfer_bytes_per_window: usize,
+    pub hybrid_result_count_total: usize,
+    pub hybrid_result_hash_total: String,
+    pub equivalent_to_baseline: Option<bool>,
+    pub metadata: ReproMetadata,
+
+    // Additional requested metrics
+    pub wall_clock_benchmark_duration_ms: u64,
+    pub wall_clock_overhead_ms: f64,
+    pub uses_virtual_event_time: bool,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct SustainedSummaryRow {
+    pub system: String,
+    pub mode: String,
+    pub time_mode: String,
+    pub runs: usize,
+    pub historical_events: usize,
+    pub logical_live_duration_seconds: usize,
+    pub event_rate_hz: usize,
+    pub event_interval_ms: f64,
+    pub expected_wall_clock_duration_ms: u64,
+    pub window_size_ms: usize,
+    pub window_slide_ms: usize,
+    pub avg_events_published: f64,
+    pub avg_events_processed: f64,
+    pub avg_completed_windows_total: f64,
+    pub avg_completed_windows_in_horizon: f64,
+    pub avg_flush_windows: f64,
+    pub avg_missed_windows: f64,
+    pub p50_first_hybrid_result_latency_ms: f64,
+    pub p95_first_hybrid_result_latency_ms: f64,
+    pub p50_first_hybrid_result_wall_clock_ms: f64,
+    pub p95_first_hybrid_result_wall_clock_ms: f64,
+    pub p50_window_hybrid_latency_ms: f64,
+    pub p95_window_hybrid_latency_ms: f64,
+    pub p50_window_result_wall_clock_offset_ms: f64,
+    pub p95_window_result_wall_clock_offset_ms: f64,
+    pub avg_historical_preparation_latency_ms: f64,
+    pub avg_first_live_window_latency_ms: f64,
+    pub avg_readiness_gap_ms: f64,
+    pub avg_hybrid_wait_after_inputs_ready_ms: f64,
+    pub avg_external_join_latency_total_ms: f64,
+    pub avg_external_join_latency_ms: f64,
+    pub avg_estimated_external_transfer_bytes_total: f64,
+    pub avg_estimated_external_transfer_bytes_per_window: f64,
+    pub avg_hybrid_result_count_total: f64,
+    pub avg_wall_clock_benchmark_duration_ms: f64,
+    pub avg_wall_clock_overhead_ms: f64,
+    pub uses_virtual_event_time: bool,
+    pub equivalence_rate: f64,
+}
+
+#[derive(Clone)]
+pub struct SustainedWorkload {
+    pub historical_storage: Arc<StreamingSegmentedStorage>,
+    pub historical_rdf_events: Vec<RDFEvent>,
+    pub live_events: Vec<RDFEvent>,
+    pub historical_start_ts: u64,
+    pub historical_end_ts: u64,
+    pub historical_sparql_query: String,
+    pub hybrid_query: String,
+}
+
+pub struct SustainedPair {
+    pub unified: SustainedRow,
+    pub decomposed: SustainedRow,
+}
+
+pub struct SustainedRunConfig<'a> {
+    pub mode: ExecutionMode,
+    pub time_mode: TimeMode,
+    pub run_index: usize,
+    pub is_warmup: bool,
+    pub historical_events: usize,
+    pub live_duration_seconds: usize,
+    pub event_rate_hz: usize,
+    pub event_interval_ms: f64,
+    pub expected_wall_clock_duration_ms: u64,
+    pub window_size_seconds: usize,
+    pub window_slide_seconds: usize,
+    pub metadata: &'a ReproMetadata,
+    pub adapter: &'a dyn ExternalHistoricalAdapter,
+    pub warm_workload: Option<&'a SustainedWorkload>,
+    pub debug_output_dir: Option<&'a Path>,
+}
+
+impl<'a> SustainedRunConfig<'a> {
+    pub fn expected_completed_windows_in_horizon(&self) -> usize {
+        let d = self.live_duration_seconds;
+        let w = self.window_size_seconds;
+        let s = self.window_slide_seconds;
+        if d == 0 {
+            return 0;
+        }
+        let first_end_sec = w + s - 1;
+        if d >= first_end_sec {
+            1 + (d - first_end_sec) / s
+        } else {
+            0
+        }
+    }
+}
+
+pub fn sustained_event_interval_ms(event_rate_hz: usize) -> f64 {
+    1000.0 / event_rate_hz as f64
+}
+
+pub fn sustained_expected_wall_clock_duration_ms(live_duration_seconds: usize) -> u64 {
+    (live_duration_seconds as u64) * 1000
+}
+
+pub struct SustainedSystemOutput {
+    pub row: SustainedRow,
+    pub window_results: HashMap<String, Vec<HashMap<String, String>>>,
+    pub live_events: Vec<RDFEvent>,
+    pub historical_baseline: Vec<HashMap<String, String>>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct BindingWithWindow {
+    pub bindings: HashMap<String, String>,
+    pub window_start_ms: u64,
+    pub window_end_ms: u64,
+    pub window_id: String,
+}
+
+pub struct SustainedLiveCollectionResult {
+    pub first_result_engine_ms: u64,
+    pub bindings: Vec<BindingWithWindow>,
+}
+
+fn canonical_window_hash(
+    rows: &[HashMap<String, String>],
+) -> Result<String, Box<dyn std::error::Error>> {
+    let mut canonical_rows = rows.iter().map(canonicalize_row).collect::<Vec<_>>();
+    canonical_rows.sort();
+    let payload = serde_json::to_vec(&canonical_rows)?;
+    let digest = Sha256::digest(payload);
+    Ok(format!("{digest:x}"))
+}
+
+fn canonical_result_hash_sustained(
+    windows: &HashMap<String, Vec<HashMap<String, String>>>,
+) -> Result<String, Box<dyn std::error::Error>> {
+    let mut keys: Vec<String> = windows.keys().cloned().collect();
+    keys.sort_unstable();
+    let mut all_canonical = Vec::new();
+    for key in keys {
+        let rows = &windows[&key];
+        let mut canonical_rows = rows.iter().map(canonicalize_row).collect::<Vec<_>>();
+        canonical_rows.sort();
+        all_canonical.push((key, canonical_rows));
+    }
+    let payload = serde_json::to_vec(&all_canonical)?;
+    let digest = Sha256::digest(payload);
+    Ok(format!("{digest:x}"))
+}
+
+pub fn build_sustained_live_events(
+    duration_sec: usize,
+    rate_hz: usize,
+    start_ts: u64,
+) -> Vec<RDFEvent> {
+    let total_events = duration_sec * rate_hz;
+    if total_events == 0 {
+        return Vec::new();
+    }
+    let interval_ms = 1000 / rate_hz;
+    (0..total_events)
+        .map(|index| {
+            RDFEvent::new(
+                start_ts + (index * interval_ms) as u64,
+                &format!("http://example.org/junction/{}", index % 64),
+                TRAFFIC_PREDICATE,
+                &(70 + (index % 11)).to_string(),
+                GRAPH_URI,
+            )
+        })
+        .collect()
+}
+
+fn parse_window_id(window_id: &str) -> Option<(u64, u64)> {
+    let mut parts = window_id.split('-');
+    let start = parts.next()?.parse().ok()?;
+    let end = parts.next()?.parse().ok()?;
+    Some((start, end))
+}
+
+fn wait_for_sustained_event_schedule(
+    config: &SustainedRunConfig<'_>,
+    replay_start: Instant,
+    event_index: usize,
+) {
+    if config.time_mode != TimeMode::WallClock {
+        return;
+    }
+    let target =
+        replay_start + Duration::from_secs_f64(event_index as f64 / config.event_rate_hz as f64);
+    if let Some(remaining) = target.checked_duration_since(Instant::now()) {
+        std::thread::sleep(remaining);
+    }
+}
+
+fn wait_for_sustained_replay_flush(config: &SustainedRunConfig<'_>, replay_deadline: Instant) {
+    if config.time_mode != TimeMode::WallClock {
+        return;
+    }
+    if let Some(remaining) = replay_deadline.checked_duration_since(Instant::now()) {
+        std::thread::sleep(remaining);
+    }
+}
+
+fn sustained_hybrid_query(
+    start_ts: u64,
+    end_ts: u64,
+    window_size_ms: usize,
+    window_slide_ms: usize,
+) -> String {
+    format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+        PREFIX baseline: <{BASELINE_NS}>
+
+        REGISTER RStream <output> AS
+        SELECT ?sensor ?liveFlow ?baselineFlow
+        FROM NAMED WINDOW ex:hist ON STREAM <{GRAPH_URI}> [START {start_ts} END {end_ts}]
+        FROM NAMED WINDOW ex:live ON STREAM <{LIVE_STREAM_URI}> [RANGE {window_size_ms} STEP {window_slide_ms}]
+        USING BASELINE ex:hist AGGREGATE
+        WHERE {{
+            WINDOW ex:hist {{
+                ?sensor ex:baselineFlow ?baselineFlow .
+            }}
+            WINDOW ex:live {{
+                ?sensor ex:trafficFlow ?liveFlow .
+            }}
+            ?sensor baseline:baselineFlow ?baselineFlow .
+        }}
+        "#
+    )
+}
+
+fn live_only_rspql_sustained(window_size_ms: usize, window_slide_ms: usize) -> String {
+    format!(
+        r#"
+        PREFIX ex: <http://example.org/>
+
+        REGISTER RStream <output> AS
+        SELECT ?sensor ?liveFlow
+        FROM NAMED WINDOW ex:live ON STREAM <{LIVE_STREAM_URI}> [RANGE {window_size_ms} STEP {window_slide_ms}]
+        WHERE {{
+            WINDOW ex:live {{
+                ?sensor ex:trafficFlow ?liveFlow .
+            }}
+        }}
+        "#
+    )
+}
+
+pub fn prepare_sustained_workload(
+    historical_events: usize,
+    live_duration_seconds: usize,
+    event_rate_hz: usize,
+    window_size_seconds: usize,
+    window_slide_seconds: usize,
+) -> Result<SustainedWorkload, Box<dyn std::error::Error>> {
+    let historical_start_ts = 1_800_000_000_000;
+    let historical_storage = build_historical_storage(historical_events, historical_start_ts)?;
+    let historical_rdf_events = historical_storage.query_rdf(
+        historical_start_ts,
+        historical_start_ts + historical_events.saturating_sub(1) as u64,
+    )?;
+    let live_events =
+        build_sustained_live_events(live_duration_seconds, event_rate_hz, 1_900_000_000_000);
+    let window_size_ms = window_size_seconds * 1000;
+    let window_slide_ms = window_slide_seconds * 1000;
+
+    Ok(SustainedWorkload {
+        historical_storage,
+        historical_rdf_events,
+        live_events,
+        historical_start_ts,
+        historical_end_ts: historical_start_ts + historical_events.saturating_sub(1) as u64,
+        historical_sparql_query: historical_baseline_sparql_query()?,
+        hybrid_query: sustained_hybrid_query(
+            historical_start_ts,
+            historical_start_ts + historical_events.saturating_sub(1) as u64,
+            window_size_ms,
+            window_slide_ms,
+        ),
+    })
+}
+
+pub fn run_sustained_pair(
+    config: SustainedRunConfig<'_>,
+) -> Result<SustainedPair, Box<dyn std::error::Error>> {
+    let unified = run_sustained_system(CoordinationSystem::JanusUnified, &config)?;
+    let decomposed = run_sustained_system(CoordinationSystem::DecomposedOxigraph, &config)?;
+
+    let mut unified_row = unified.row.clone();
+    let mut decomposed_row = decomposed.row.clone();
+
+    let expected_completed_windows = config.expected_completed_windows_in_horizon();
+    let mut equivalent = unified_row.completed_windows_in_horizon
+        == decomposed_row.completed_windows_in_horizon
+        && unified_row.completed_windows_in_horizon == expected_completed_windows
+        && unified_row.hybrid_result_hash_total == decomposed_row.hybrid_result_hash_total
+        && !unified_row.hybrid_result_hash_total.is_empty()
+        && unified_row.hybrid_result_hash_total
+            != "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855";
+
+    if equivalent {
+        let horizon_end_ms = i64::try_from(
+            unified_row
+                .first_live_event_at
+                .saturating_add((config.live_duration_seconds * 1000) as u64),
+        )
+        .map_err(|_| "horizon end timestamp exceeds i64 range")?;
+        for (win_id, u_rows) in &unified.window_results {
+            let parts: Vec<&str> = win_id.split('-').collect();
+            if parts.len() == 2 {
+                if let Ok(win_end) = parts[1].parse::<i64>() {
+                    if win_end > horizon_end_ms {
+                        continue;
+                    }
+                }
+            }
+            if let Some(d_rows) = decomposed.window_results.get(win_id) {
+                let u_hash = canonical_window_hash(u_rows)?;
+                let d_hash = canonical_window_hash(d_rows)?;
+                if u_hash != d_hash || u_rows.len() != d_rows.len() {
+                    equivalent = false;
+                    break;
+                }
+            } else {
+                equivalent = false;
+                break;
+            }
+        }
+    }
+
+    unified_row.equivalent_to_baseline = Some(equivalent);
+    decomposed_row.equivalent_to_baseline = None;
+
+    if let Some(debug_output_dir) = config.debug_output_dir {
+        write_h1_2_debug_artifacts(debug_output_dir, &unified, &decomposed, &config, equivalent)?;
+    }
+
+    Ok(SustainedPair { unified: unified_row, decomposed: decomposed_row })
+}
+
+fn run_sustained_system(
+    system: CoordinationSystem,
+    config: &SustainedRunConfig<'_>,
+) -> Result<SustainedSystemOutput, Box<dyn std::error::Error>> {
+    let owned_workload;
+    let workload = if config.mode == ExecutionMode::Warm {
+        config.warm_workload.ok_or("warm mode requires prepared workload")?
+    } else {
+        owned_workload = prepare_sustained_workload(
+            config.historical_events,
+            config.live_duration_seconds,
+            config.event_rate_hz,
+            config.window_size_seconds,
+            config.window_slide_seconds,
+        )?;
+        &owned_workload
+    };
+
+    let start_wall = Instant::now();
+    let client_start = now_ms();
+    let parser = JanusQLParser::new()?;
+    let parsed = parser.parse(&workload.hybrid_query)?;
+    let query_registered = now_ms();
+
+    let historical_start = now_ms();
+    let executor =
+        HistoricalExecutor::new(Arc::clone(&workload.historical_storage), OxigraphAdapter::new());
+    let baseline_bindings = executor.execute_fixed_window(
+        parsed.historical_windows.first().ok_or("missing historical window")?,
+        &workload.historical_sparql_query,
+    )?;
+    let historical_done = now_ms();
+
+    let events_published = workload.live_events.len();
+    let events_processed = workload.live_events.len();
+    let window_size_ms = config.window_size_seconds * 1000;
+    let window_slide_ms = config.window_slide_seconds * 1000;
+    let expected_completed_windows = config.expected_completed_windows_in_horizon();
+    let live_first_event_at = workload.live_events.first().map(|e| e.timestamp).unwrap_or(0);
+    let horizon_end_ms = i64::try_from(
+        live_first_event_at.saturating_add((config.live_duration_seconds * 1000) as u64),
+    )
+    .map_err(|_| "horizon end timestamp exceeds i64 range")?;
+
+    let mut window_results = HashMap::<String, Vec<HashMap<String, String>>>::new();
+    let mut window_hybrid_latencies = Vec::<(i64, f64)>::new();
+    let mut window_wall_clock_offsets = HashMap::<String, f64>::new();
+    let mut first_live_window_ready_at = 0u64;
+    let mut first_hybrid_result_at = 0u64;
+    let mut first_hybrid_result_wall_clock_ms = 0.0;
+
+    let live_start_at;
+    let mut external_join_latencies = Vec::<(i64, f64)>::new();
+    let mut live_rows_count = 0;
+    let historical_baseline;
+
+    let estimated_external_transfer_bytes_total;
+
+    match system {
+        CoordinationSystem::JanusUnified => {
+            let mut processor = LiveStreamProcessing::new(parsed.rspql_query.clone())?;
+            processor.register_stream(LIVE_STREAM_URI)?;
+            materialize_bindings_as_static_baseline(&mut processor, &baseline_bindings)?;
+            processor.start_processing()?;
+            live_start_at = now_ms();
+            let replay_start = Instant::now();
+            let replay_deadline =
+                replay_start + Duration::from_millis(config.expected_wall_clock_duration_ms);
+
+            historical_baseline = baseline_statements_from_bindings(&baseline_bindings)
+                .into_iter()
+                .map(|(s, p, o)| {
+                    HashMap::from([("sensor".to_string(), s), ("baselineFlow".to_string(), o)])
+                })
+                .collect();
+            estimated_external_transfer_bytes_total = 0;
+
+            for (event_index, event) in workload.live_events.iter().enumerate() {
+                wait_for_sustained_event_schedule(config, replay_start, event_index);
+                let start_add = Instant::now();
+                processor.add_event(LIVE_STREAM_URI, event.clone())?;
+                let add_duration = start_add.elapsed().as_secs_f64() * 1000.0;
+
+                std::thread::sleep(std::time::Duration::from_millis(2));
+
+                let mut received = Vec::new();
+                while let Some(res) = processor.try_receive_result()? {
+                    received.push(res);
+                }
+
+                if !received.is_empty() {
+                    let now = now_ms();
+                    let wall_clock_offset_ms = replay_start.elapsed().as_secs_f64() * 1000.0;
+                    if first_live_window_ready_at == 0 {
+                        first_live_window_ready_at = now;
+                        first_hybrid_result_at = now;
+                        first_hybrid_result_wall_clock_ms = wall_clock_offset_ms;
+                    }
+                    for res in received {
+                        let win_start = res.timestamp_from;
+                        let win_end = res.timestamp_to;
+                        let win_id = format!("{}-{}", win_start, win_end);
+                        let rows = parse_rsprs_binding_string(&res.bindings);
+                        window_results.entry(win_id.clone()).or_default().push(rows);
+                        window_wall_clock_offsets.entry(win_id).or_insert(wall_clock_offset_ms);
+                        window_hybrid_latencies.push((win_end, add_duration));
+                    }
+                }
+            }
+
+            wait_for_sustained_replay_flush(config, replay_deadline);
+            let close_start = Instant::now();
+            let close_ts = workload.live_events.last().map_or(20_000_i64, |e| {
+                i64::try_from(e.timestamp).unwrap_or(i64::MAX).saturating_add(20_000)
+            });
+            processor.close_stream(LIVE_STREAM_URI, close_ts)?;
+            let close_duration = close_start.elapsed().as_secs_f64() * 1000.0;
+
+            std::thread::sleep(std::time::Duration::from_millis(10));
+
+            let mut final_received = Vec::new();
+            while let Some(res) = processor.try_receive_result()? {
+                final_received.push(res);
+            }
+            if !final_received.is_empty() {
+                let now = now_ms();
+                let wall_clock_offset_ms = replay_start.elapsed().as_secs_f64() * 1000.0;
+                if first_live_window_ready_at == 0 {
+                    first_live_window_ready_at = now;
+                    first_hybrid_result_at = now;
+                    first_hybrid_result_wall_clock_ms = wall_clock_offset_ms;
+                }
+                for res in final_received {
+                    let win_start = res.timestamp_from;
+                    let win_end = res.timestamp_to;
+                    let win_id = format!("{}-{}", win_start, win_end);
+                    let rows = parse_rsprs_binding_string(&res.bindings);
+                    window_results.entry(win_id.clone()).or_default().push(rows);
+                    window_wall_clock_offsets.entry(win_id).or_insert(wall_clock_offset_ms);
+                    window_hybrid_latencies.push((win_end, close_duration));
+                }
+            }
+        }
+        CoordinationSystem::DecomposedOxigraph => {
+            let external_bindings = config.adapter.execute_bindings_query(
+                &workload.historical_sparql_query,
+                &workload.historical_rdf_events,
+            )?;
+            let materialized_baseline_rows =
+                materialized_baseline_rows_from_bindings(&external_bindings, "baselineFlow");
+            let historical_done = now_ms();
+
+            historical_baseline = materialized_baseline_rows.clone();
+            let historical_intermediate_bytes = serde_json::to_vec(&external_bindings)?.len();
+
+            let mut processor = LiveStreamProcessing::new(live_only_rspql_sustained(
+                window_size_ms,
+                window_slide_ms,
+            ))?;
+            processor.register_stream(LIVE_STREAM_URI)?;
+            processor.start_processing()?;
+            live_start_at = now_ms();
+            let replay_start = Instant::now();
+            let replay_deadline =
+                replay_start + Duration::from_millis(config.expected_wall_clock_duration_ms);
+
+            let mut all_live_rows = Vec::new();
+
+            for (event_index, event) in workload.live_events.iter().enumerate() {
+                wait_for_sustained_event_schedule(config, replay_start, event_index);
+                let start_add = Instant::now();
+                processor.add_event(LIVE_STREAM_URI, event.clone())?;
+                let add_duration = start_add.elapsed().as_secs_f64() * 1000.0;
+
+                std::thread::sleep(std::time::Duration::from_millis(2));
+
+                let mut received = Vec::new();
+                while let Some(res) = processor.try_receive_result()? {
+                    received.push(res);
+                }
+
+                if !received.is_empty() {
+                    let now = now_ms();
+                    let wall_clock_offset_ms = replay_start.elapsed().as_secs_f64() * 1000.0;
+                    if first_live_window_ready_at == 0 {
+                        first_live_window_ready_at = now;
+                    }
+                    for res in received {
+                        let win_start = res.timestamp_from;
+                        let win_end = res.timestamp_to;
+                        let win_id = format!("{}-{}", win_start, win_end);
+                        let rows = parse_rsprs_binding_string(&res.bindings);
+                        if win_end <= horizon_end_ms {
+                            all_live_rows.push(rows.clone());
+                        }
+                        live_rows_count += 1;
+
+                        let start_join = Instant::now();
+                        let joined = join_live_with_baseline(&[rows], &materialized_baseline_rows);
+                        let join_duration = start_join.elapsed().as_secs_f64() * 1000.0;
+                        if first_hybrid_result_at == 0 {
+                            first_hybrid_result_at = now_ms();
+                            first_hybrid_result_wall_clock_ms = wall_clock_offset_ms;
+                        }
+
+                        for row in joined {
+                            window_results.entry(win_id.clone()).or_default().push(row);
+                        }
+                        window_wall_clock_offsets.entry(win_id).or_insert(wall_clock_offset_ms);
+
+                        window_hybrid_latencies.push((win_end, add_duration + join_duration));
+                        external_join_latencies.push((win_end, join_duration));
+                    }
+                }
+            }
+
+            wait_for_sustained_replay_flush(config, replay_deadline);
+            let close_start = Instant::now();
+            let close_ts = workload.live_events.last().map_or(20_000_i64, |e| {
+                i64::try_from(e.timestamp).unwrap_or(i64::MAX).saturating_add(20_000)
+            });
+            processor.close_stream(LIVE_STREAM_URI, close_ts)?;
+            let close_duration = close_start.elapsed().as_secs_f64() * 1000.0;
+
+            std::thread::sleep(std::time::Duration::from_millis(10));
+
+            let mut final_received = Vec::new();
+            while let Some(res) = processor.try_receive_result()? {
+                final_received.push(res);
+            }
+            if !final_received.is_empty() {
+                let now = now_ms();
+                let wall_clock_offset_ms = replay_start.elapsed().as_secs_f64() * 1000.0;
+                if first_live_window_ready_at == 0 {
+                    first_live_window_ready_at = now;
+                }
+                for res in final_received {
+                    let win_start = res.timestamp_from;
+                    let win_end = res.timestamp_to;
+                    let win_id = format!("{}-{}", win_start, win_end);
+                    let rows = parse_rsprs_binding_string(&res.bindings);
+                    if win_end <= horizon_end_ms {
+                        all_live_rows.push(rows.clone());
+                    }
+                    live_rows_count += 1;
+
+                    let start_join = Instant::now();
+                    let joined = join_live_with_baseline(&[rows], &materialized_baseline_rows);
+                    let join_duration = start_join.elapsed().as_secs_f64() * 1000.0;
+                    if first_hybrid_result_at == 0 {
+                        first_hybrid_result_at = now_ms();
+                        first_hybrid_result_wall_clock_ms = wall_clock_offset_ms;
+                    }
+
+                    for row in joined {
+                        window_results.entry(win_id.clone()).or_default().push(row);
+                    }
+                    window_wall_clock_offsets.entry(win_id).or_insert(wall_clock_offset_ms);
+
+                    window_hybrid_latencies.push((win_end, close_duration + join_duration));
+                    external_join_latencies.push((win_end, join_duration));
+                }
+            }
+
+            let live_intermediate_bytes = serde_json::to_vec(&all_live_rows)?.len();
+            estimated_external_transfer_bytes_total =
+                historical_intermediate_bytes + live_intermediate_bytes;
+        }
+    }
+
+    let wall_clock_benchmark_duration_ms = start_wall.elapsed().as_millis() as u64;
+
+    let completed_windows_total = window_results.len();
+    let mut completed_windows_in_horizon = 0;
+    let mut horizon_window_results = HashMap::new();
+    for (win_id, rows) in &window_results {
+        let parts: Vec<&str> = win_id.split('-').collect();
+        if parts.len() == 2 {
+            if let Ok(win_end) = parts[1].parse::<i64>() {
+                if win_end <= horizon_end_ms {
+                    completed_windows_in_horizon += 1;
+                    horizon_window_results.insert(win_id.clone(), rows.clone());
+                }
+            }
+        }
+    }
+    let flush_windows = completed_windows_total - completed_windows_in_horizon;
+    let missed_windows = expected_completed_windows.saturating_sub(completed_windows_in_horizon);
+
+    let historical_preparation_latency_ms = (historical_done - historical_start) as f64;
+    let first_live_window_latency_ms = if first_live_window_ready_at > 0 {
+        (first_live_window_ready_at - live_start_at) as f64
+    } else {
+        0.0
+    };
+    let first_hybrid_result_latency_ms = if first_hybrid_result_at > 0 {
+        (first_hybrid_result_at - client_start) as f64
+    } else {
+        0.0
+    };
+
+    let readiness_gap_ms = if historical_done > 0 && first_live_window_ready_at > 0 {
+        (historical_done as f64 - first_live_window_ready_at as f64).abs()
+    } else {
+        0.0
+    };
+
+    let hybrid_wait_after_inputs_ready_ms = if first_hybrid_result_at > 0 {
+        let max_ready = historical_done.max(first_live_window_ready_at) as f64;
+        (first_hybrid_result_at as f64 - max_ready).max(0.0)
+    } else {
+        0.0
+    };
+
+    let horizon_latencies: Vec<f64> = window_hybrid_latencies
+        .iter()
+        .filter(|&&(win_end, _)| win_end <= horizon_end_ms)
+        .map(|&(_, lat)| lat)
+        .collect();
+    let p50_window_hybrid_latency_ms = percentile(&horizon_latencies, 50.0);
+    let p95_window_hybrid_latency_ms = percentile(&horizon_latencies, 95.0);
+
+    let horizon_join_latencies: Vec<f64> = external_join_latencies
+        .iter()
+        .filter(|&&(win_end, _)| win_end <= horizon_end_ms)
+        .map(|&(_, lat)| lat)
+        .collect();
+    let external_join_latency_total_ms: f64 = horizon_join_latencies.iter().sum();
+    let external_join_latency_avg_ms = if completed_windows_in_horizon > 0 {
+        external_join_latency_total_ms / completed_windows_in_horizon as f64
+    } else {
+        0.0
+    };
+
+    let estimated_external_transfer_bytes_per_window = if completed_windows_in_horizon > 0 {
+        estimated_external_transfer_bytes_total / completed_windows_in_horizon
+    } else {
+        0
+    };
+    let mut window_result_wall_clock_offsets_ms = window_wall_clock_offsets
+        .iter()
+        .filter_map(|(win_id, offset)| {
+            let (_, win_end) = parse_window_id(win_id)?;
+            (i64::try_from(win_end).ok()? <= horizon_end_ms).then_some(*offset)
+        })
+        .collect::<Vec<_>>();
+    window_result_wall_clock_offsets_ms
+        .sort_by(|left, right| left.partial_cmp(right).unwrap_or(Ordering::Equal));
+    let p50_window_result_wall_clock_offset_ms =
+        percentile(&window_result_wall_clock_offsets_ms, 50.0);
+    let p95_window_result_wall_clock_offset_ms =
+        percentile(&window_result_wall_clock_offsets_ms, 95.0);
+
+    let mut hybrid_result_count_total = 0;
+    for rows in horizon_window_results.values() {
+        hybrid_result_count_total += rows.len();
+    }
+    let hybrid_result_hash_total = canonical_result_hash_sustained(&horizon_window_results)?;
+    let wall_clock_overhead_ms =
+        wall_clock_benchmark_duration_ms as f64 - config.expected_wall_clock_duration_ms as f64;
+
+    let row = SustainedRow {
+        system: system.as_str().to_string(),
+        mode: config.mode.as_str().to_string(),
+        time_mode: config.time_mode.as_str().to_string(),
+        is_warmup: config.is_warmup,
+        run_index: config.run_index,
+        historical_events: config.historical_events,
+        logical_live_duration_seconds: config.live_duration_seconds,
+        event_rate_hz: config.event_rate_hz,
+        event_interval_ms: config.event_interval_ms,
+        expected_wall_clock_duration_ms: config.expected_wall_clock_duration_ms,
+        events_published,
+        events_processed,
+        window_size_ms,
+        window_slide_ms,
+        expected_completed_windows,
+        completed_windows_total,
+        completed_windows_in_horizon,
+        flush_windows,
+        missed_windows,
+        historical_start_at: historical_start,
+        historical_ready_at: historical_done,
+        live_start_at,
+        first_live_event_at: live_first_event_at,
+        first_live_window_ready_at,
+        first_hybrid_result_at,
+        historical_preparation_latency_ms,
+        first_live_window_latency_ms,
+        first_hybrid_result_latency_ms,
+        first_hybrid_result_wall_clock_ms,
+        readiness_gap_ms,
+        hybrid_wait_after_inputs_ready_ms,
+        p50_window_hybrid_latency_ms,
+        p95_window_hybrid_latency_ms,
+        window_result_wall_clock_offsets_ms,
+        p50_window_result_wall_clock_offset_ms,
+        p95_window_result_wall_clock_offset_ms,
+        external_join_latency_total_ms,
+        external_join_latency_avg_ms,
+        estimated_external_transfer_bytes_total,
+        estimated_external_transfer_bytes_per_window,
+        hybrid_result_count_total,
+        hybrid_result_hash_total,
+        equivalent_to_baseline: None,
+        metadata: config.metadata.clone(),
+        wall_clock_benchmark_duration_ms,
+        wall_clock_overhead_ms,
+        uses_virtual_event_time: config.time_mode.uses_virtual_event_time(),
+    };
+
+    Ok(SustainedSystemOutput {
+        row,
+        window_results,
+        live_events: workload.live_events.clone(),
+        historical_baseline,
+    })
+}
+
+pub fn summarize_sustained(rows: &[SustainedRow]) -> Vec<SustainedSummaryRow> {
+    let mut grouped = HashMap::<(String, String, String), Vec<&SustainedRow>>::new();
+    for row in rows {
+        grouped
+            .entry((row.system.clone(), row.mode.clone(), row.time_mode.clone()))
+            .or_default()
+            .push(row);
+    }
+
+    let mut summary = grouped
+        .into_iter()
+        .map(|((system, mode, time_mode), items)| {
+            let runs = items.len();
+            let equiv_count =
+                items.iter().filter(|row| row.equivalent_to_baseline == Some(true)).count();
+
+            SustainedSummaryRow {
+                system,
+                mode,
+                time_mode,
+                runs,
+                historical_events: items.first().map_or(0, |row| row.historical_events),
+                logical_live_duration_seconds: items
+                    .first()
+                    .map_or(0, |row| row.logical_live_duration_seconds),
+                event_rate_hz: items.first().map_or(0, |row| row.event_rate_hz),
+                event_interval_ms: items.first().map_or(0.0, |row| row.event_interval_ms),
+                expected_wall_clock_duration_ms: items
+                    .first()
+                    .map_or(0, |row| row.expected_wall_clock_duration_ms),
+                window_size_ms: items.first().map_or(0, |row| row.window_size_ms),
+                window_slide_ms: items.first().map_or(0, |row| row.window_slide_ms),
+                avg_events_published: mean_usize(
+                    &items.iter().map(|row| row.events_published).collect::<Vec<_>>(),
+                ),
+                avg_events_processed: mean_usize(
+                    &items.iter().map(|row| row.events_processed).collect::<Vec<_>>(),
+                ),
+                avg_completed_windows_total: mean_usize(
+                    &items.iter().map(|row| row.completed_windows_total).collect::<Vec<_>>(),
+                ),
+                avg_completed_windows_in_horizon: mean_usize(
+                    &items.iter().map(|row| row.completed_windows_in_horizon).collect::<Vec<_>>(),
+                ),
+                avg_flush_windows: mean_usize(
+                    &items.iter().map(|row| row.flush_windows).collect::<Vec<_>>(),
+                ),
+                avg_missed_windows: mean_usize(
+                    &items.iter().map(|row| row.missed_windows).collect::<Vec<_>>(),
+                ),
+                p50_first_hybrid_result_latency_ms: percentile(
+                    &items.iter().map(|row| row.first_hybrid_result_latency_ms).collect::<Vec<_>>(),
+                    50.0,
+                ),
+                p95_first_hybrid_result_latency_ms: percentile(
+                    &items.iter().map(|row| row.first_hybrid_result_latency_ms).collect::<Vec<_>>(),
+                    95.0,
+                ),
+                p50_first_hybrid_result_wall_clock_ms: percentile(
+                    &items
+                        .iter()
+                        .map(|row| row.first_hybrid_result_wall_clock_ms)
+                        .collect::<Vec<_>>(),
+                    50.0,
+                ),
+                p95_first_hybrid_result_wall_clock_ms: percentile(
+                    &items
+                        .iter()
+                        .map(|row| row.first_hybrid_result_wall_clock_ms)
+                        .collect::<Vec<_>>(),
+                    95.0,
+                ),
+                p50_window_hybrid_latency_ms: percentile(
+                    &items.iter().map(|row| row.p50_window_hybrid_latency_ms).collect::<Vec<_>>(),
+                    50.0,
+                ),
+                p95_window_hybrid_latency_ms: percentile(
+                    &items.iter().map(|row| row.p95_window_hybrid_latency_ms).collect::<Vec<_>>(),
+                    95.0,
+                ),
+                p50_window_result_wall_clock_offset_ms: percentile(
+                    &items
+                        .iter()
+                        .map(|row| row.p50_window_result_wall_clock_offset_ms)
+                        .collect::<Vec<_>>(),
+                    50.0,
+                ),
+                p95_window_result_wall_clock_offset_ms: percentile(
+                    &items
+                        .iter()
+                        .map(|row| row.p95_window_result_wall_clock_offset_ms)
+                        .collect::<Vec<_>>(),
+                    95.0,
+                ),
+                avg_historical_preparation_latency_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.historical_preparation_latency_ms)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_first_live_window_latency_ms: mean(
+                    &items.iter().map(|row| row.first_live_window_latency_ms).collect::<Vec<_>>(),
+                ),
+                avg_readiness_gap_ms: mean(
+                    &items.iter().map(|row| row.readiness_gap_ms).collect::<Vec<_>>(),
+                ),
+                avg_hybrid_wait_after_inputs_ready_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.hybrid_wait_after_inputs_ready_ms)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_external_join_latency_total_ms: mean(
+                    &items.iter().map(|row| row.external_join_latency_total_ms).collect::<Vec<_>>(),
+                ),
+                avg_external_join_latency_ms: mean(
+                    &items.iter().map(|row| row.external_join_latency_avg_ms).collect::<Vec<_>>(),
+                ),
+                avg_estimated_external_transfer_bytes_total: mean_usize(
+                    &items
+                        .iter()
+                        .map(|row| row.estimated_external_transfer_bytes_total)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_estimated_external_transfer_bytes_per_window: mean_usize(
+                    &items
+                        .iter()
+                        .map(|row| row.estimated_external_transfer_bytes_per_window)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_hybrid_result_count_total: mean_usize(
+                    &items.iter().map(|row| row.hybrid_result_count_total).collect::<Vec<_>>(),
+                ),
+                avg_wall_clock_benchmark_duration_ms: mean(
+                    &items
+                        .iter()
+                        .map(|row| row.wall_clock_benchmark_duration_ms as f64)
+                        .collect::<Vec<_>>(),
+                ),
+                avg_wall_clock_overhead_ms: mean(
+                    &items.iter().map(|row| row.wall_clock_overhead_ms).collect::<Vec<_>>(),
+                ),
+                uses_virtual_event_time: items
+                    .first()
+                    .map_or(true, |row| row.uses_virtual_event_time),
+                equivalence_rate: if runs > 0 {
+                    equiv_count as f64 / runs as f64
+                } else {
+                    0.0
+                },
+            }
+        })
+        .collect::<Vec<_>>();
+    summary.sort_by(|left, right| {
+        left.system
+            .cmp(&right.system)
+            .then_with(|| left.mode.cmp(&right.mode))
+            .then_with(|| left.time_mode.cmp(&right.time_mode))
+    });
+    summary
+}
+
+pub fn write_sustained_summary_csv(
+    path: &Path,
+    rows: &[SustainedSummaryRow],
+) -> std::io::Result<()> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "system,mode,time_mode,runs,historical_events,logical_live_duration_seconds,event_rate_hz,event_interval_ms,expected_wall_clock_duration_ms,window_size_ms,window_slide_ms,avg_events_published,avg_events_processed,avg_completed_windows_total,avg_completed_windows_in_horizon,avg_flush_windows,avg_missed_windows,p50_first_hybrid_result_latency_ms,p95_first_hybrid_result_latency_ms,p50_first_hybrid_result_wall_clock_ms,p95_first_hybrid_result_wall_clock_ms,p50_window_hybrid_latency_ms,p95_window_hybrid_latency_ms,p50_window_result_wall_clock_offset_ms,p95_window_result_wall_clock_offset_ms,avg_historical_preparation_latency_ms,avg_first_live_window_latency_ms,avg_readiness_gap_ms,avg_hybrid_wait_after_inputs_ready_ms,avg_external_join_latency_total_ms,avg_external_join_latency_ms,avg_estimated_external_transfer_bytes_total,avg_estimated_external_transfer_bytes_per_window,avg_hybrid_result_count_total,avg_wall_clock_benchmark_duration_ms,avg_wall_clock_overhead_ms,uses_virtual_event_time,equivalence_rate"
+    )?;
+    for row in rows {
+        writeln!(
+            file,
+            "{},{},{},{},{},{},{},{:.3},{},{},{},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{},{:.3}",
+            row.system,
+            row.mode,
+            row.time_mode,
+            row.runs,
+            row.historical_events,
+            row.logical_live_duration_seconds,
+            row.event_rate_hz,
+            row.event_interval_ms,
+            row.expected_wall_clock_duration_ms,
+            row.window_size_ms,
+            row.window_slide_ms,
+            row.avg_events_published,
+            row.avg_events_processed,
+            row.avg_completed_windows_total,
+            row.avg_completed_windows_in_horizon,
+            row.avg_flush_windows,
+            row.avg_missed_windows,
+            row.p50_first_hybrid_result_latency_ms,
+            row.p95_first_hybrid_result_latency_ms,
+            row.p50_first_hybrid_result_wall_clock_ms,
+            row.p95_first_hybrid_result_wall_clock_ms,
+            row.p50_window_hybrid_latency_ms,
+            row.p95_window_hybrid_latency_ms,
+            row.p50_window_result_wall_clock_offset_ms,
+            row.p95_window_result_wall_clock_offset_ms,
+            row.avg_historical_preparation_latency_ms,
+            row.avg_first_live_window_latency_ms,
+            row.avg_readiness_gap_ms,
+            row.avg_hybrid_wait_after_inputs_ready_ms,
+            row.avg_external_join_latency_total_ms,
+            row.avg_external_join_latency_ms,
+            row.avg_estimated_external_transfer_bytes_total,
+            row.avg_estimated_external_transfer_bytes_per_window,
+            row.avg_hybrid_result_count_total,
+            row.avg_wall_clock_benchmark_duration_ms,
+            row.avg_wall_clock_overhead_ms,
+            row.uses_virtual_event_time,
+            row.equivalence_rate
+        )?;
+    }
+    Ok(())
+}
+
+fn write_h1_2_debug_artifacts(
+    base_dir: &Path,
+    unified: &SustainedSystemOutput,
+    decomposed: &SustainedSystemOutput,
+    config: &SustainedRunConfig<'_>,
+    equivalent: bool,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let run_dir = base_dir.join("h1_2_sustained_debug").join(format!(
+        "run_{:03}_{}",
+        config.run_index,
+        if config.is_warmup {
+            "warmup"
+        } else {
+            "measured"
+        }
+    ));
+    fs::create_dir_all(&run_dir)?;
+
+    write_jsonl(&run_dir.join("live_events.jsonl"), &event_payload_rows(&unified.live_events))?;
+    write_jsonl(&run_dir.join("historical_baseline.jsonl"), &unified.historical_baseline)?;
+
+    // Write janus_window_results.jsonl
+    let mut janus_rows = Vec::new();
+    for (win_id, rows) in &unified.window_results {
+        let parts: Vec<&str> = win_id.split('-').collect();
+        let win_start_val = parts[0].parse::<u64>().unwrap_or(0);
+        let win_end_val = parts[1].parse::<u64>().unwrap_or(0);
+        let win_hash = canonical_window_hash(rows)?;
+        janus_rows.push(serde_json::json!({
+            "window_start_ms": win_start_val,
+            "window_end_ms": win_end_val,
+            "window_id": win_id.clone(),
+            "result_count": rows.len(),
+            "result_hash": win_hash,
+            "results": rows
+        }));
+    }
+    janus_rows.sort_by_key(|val| val["window_start_ms"].as_u64().unwrap_or(0));
+    write_jsonl(&run_dir.join("janus_window_results.jsonl"), &janus_rows)?;
+
+    // Write decomposed_window_results.jsonl
+    let mut decomposed_rows = Vec::new();
+    for (win_id, rows) in &decomposed.window_results {
+        let parts: Vec<&str> = win_id.split('-').collect();
+        let win_start_val = parts[0].parse::<u64>().unwrap_or(0);
+        let win_end_val = parts[1].parse::<u64>().unwrap_or(0);
+        let win_hash = canonical_window_hash(rows)?;
+        decomposed_rows.push(serde_json::json!({
+            "window_start_ms": win_start_val,
+            "window_end_ms": win_end_val,
+            "window_id": win_id.clone(),
+            "result_count": rows.len(),
+            "result_hash": win_hash,
+            "results": rows
+        }));
+    }
+    decomposed_rows.sort_by_key(|val| val["window_start_ms"].as_u64().unwrap_or(0));
+    write_jsonl(&run_dir.join("decomposed_window_results.jsonl"), &decomposed_rows)?;
+
+    // Write per_window_equivalence.jsonl
+    let mut equivalence_rows = Vec::new();
+    let mut per_window_summary = Vec::new();
+    let mut all_keys: HashSet<String> = unified.window_results.keys().cloned().collect();
+    all_keys.extend(decomposed.window_results.keys().cloned());
+    let mut sorted_keys: Vec<String> = all_keys.into_iter().collect();
+    sorted_keys
+        .sort_by_key(|k| k.split('-').next().and_then(|s| s.parse::<u64>().ok()).unwrap_or(0));
+
+    for win_id in sorted_keys {
+        let parts: Vec<&str> = win_id.split('-').collect();
+        let win_start_val = parts[0].parse::<u64>().unwrap_or(0);
+        let win_end_val = parts[1].parse::<u64>().unwrap_or(0);
+
+        let u_rows = unified.window_results.get(&win_id);
+        let d_rows = decomposed.window_results.get(&win_id);
+        let u_len = u_rows.map(|r| r.len()).unwrap_or(0);
+        let d_len = d_rows.map(|r| r.len()).unwrap_or(0);
+        let u_hash =
+            u_rows.map(|r| canonical_window_hash(r).unwrap_or_default()).unwrap_or_default();
+        let d_hash =
+            d_rows.map(|r| canonical_window_hash(r).unwrap_or_default()).unwrap_or_default();
+        let equivalent = u_len == d_len && u_hash == d_hash && u_len > 0;
+
+        equivalence_rows.push(serde_json::json!({
+            "window_start_ms": win_start_val,
+            "window_end_ms": win_end_val,
+            "window_id": win_id.clone(),
+            "janus_count": u_len,
+            "decomposed_count": d_len,
+            "janus_hash": u_hash,
+            "decomposed_hash": d_hash,
+            "equivalent": equivalent
+        }));
+
+        per_window_summary.push(serde_json::json!({
+            "window_id": win_id,
+            "equivalent": equivalent
+        }));
+    }
+    write_jsonl(&run_dir.join("per_window_equivalence.jsonl"), &equivalence_rows)?;
+
+    // Write equivalence_report.json
+    let report = serde_json::json!({
+        "system_pair": "janus_unified_vs_decomposed_sustained",
+        "run_index": config.run_index,
+        "mode": config.mode.as_str().to_string(),
+        "time_mode": config.time_mode.as_str().to_string(),
+        "expected_windows": config.expected_completed_windows_in_horizon(),
+        "janus_completed_windows": unified.row.completed_windows_in_horizon,
+        "decomposed_completed_windows": decomposed.row.completed_windows_in_horizon,
+        "janus_total_hash": unified.row.hybrid_result_hash_total,
+        "decomposed_total_hash": decomposed.row.hybrid_result_hash_total,
+        "equivalent": equivalent,
+        "per_window_equivalence": per_window_summary
+    });
+    fs::write(run_dir.join("equivalence_report.json"), serde_json::to_vec_pretty(&report)?)?;
+
+    Ok(())
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::paper_bench::external::OxigraphExternalAdapter;
+
+    fn test_metadata() -> ReproMetadata {
+        ReproMetadata {
+            git_commit_sha: "test".to_string(),
+            branch: "test".to_string(),
+            rustc_version: "test".to_string(),
+            os: "test".to_string(),
+            cpu_model: "test".to_string(),
+            ram_bytes: Some(1),
+            benchmark_command: "test".to_string(),
+            timestamp_unix_ms: 0,
+        }
+    }
+
+    #[test]
+    fn tiny_h1_equivalence_matches_between_janus_and_oxigraph() {
+        let metadata = test_metadata();
+        let adapter = OxigraphExternalAdapter::new();
+        let workload = prepare_coordination_workload(1, 1).expect("workload should build");
+        let pair = run_coordination_pair(CoordinationRunConfig {
+            mode: ExecutionMode::Warm,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 1,
+            live_events: 1,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload),
+            debug_output_dir: None,
+        })
+        .expect("pair should run");
+
+        assert_eq!(pair.unified.result_count, 1);
+        assert_eq!(pair.decomposed.result_count, 1);
+        assert_eq!(pair.unified.result_hash, pair.decomposed.result_hash);
+        assert_eq!(pair.unified.equivalent_to_baseline, Some(true));
+    }
+
+    #[test]
+    fn test_deterministic_hybrid_dependency() {
+        let metadata = test_metadata();
+        let adapter = OxigraphExternalAdapter::new();
+
+        // 1. historical=1, live=1 -> hybrid_result_count=1
+        let workload_1_1 = prepare_coordination_workload(1, 1).expect("workload should build");
+        let pair_1_1 = run_coordination_pair(CoordinationRunConfig {
+            mode: ExecutionMode::Warm,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 1,
+            live_events: 1,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_1_1),
+            debug_output_dir: None,
+        })
+        .expect("pair should run");
+        assert_eq!(pair_1_1.unified.hybrid_result_count, 1);
+        assert_eq!(pair_1_1.decomposed.hybrid_result_count, 1);
+
+        // 2. historical=1, live=0 -> hybrid_result_count=0
+        let workload_1_0 = prepare_coordination_workload(1, 0).expect("workload should build");
+        let pair_1_0 = run_coordination_pair(CoordinationRunConfig {
+            mode: ExecutionMode::Warm,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 1,
+            live_events: 0,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_1_0),
+            debug_output_dir: None,
+        })
+        .expect("pair should run");
+        assert_eq!(pair_1_0.unified.hybrid_result_count, 0);
+        assert_eq!(pair_1_0.decomposed.hybrid_result_count, 0);
+
+        // 3. historical=0, live=1 -> hybrid_result_count=0
+        let workload_0_1 = prepare_coordination_workload(0, 1).expect("workload should build");
+        let pair_0_1 = run_coordination_pair(CoordinationRunConfig {
+            mode: ExecutionMode::Warm,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 0,
+            live_events: 1,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_0_1),
+            debug_output_dir: None,
+        })
+        .expect("pair should run");
+        assert_eq!(pair_0_1.unified.hybrid_result_count, 0);
+        assert_eq!(pair_0_1.decomposed.hybrid_result_count, 0);
+
+        // 4. historical=1, live=1 but mismatched sensor/join key -> hybrid_result_count=0
+        let mut workload_mismatched =
+            prepare_coordination_workload(1, 1).expect("workload should build");
+        // Change live event sensor to mismatched
+        if !workload_mismatched.live_events.is_empty() {
+            workload_mismatched.live_events[0] = RDFEvent::new(
+                workload_mismatched.live_events[0].timestamp,
+                "http://example.org/junction/mismatched_sensor",
+                TRAFFIC_PREDICATE,
+                &workload_mismatched.live_events[0].object,
+                GRAPH_URI,
+            );
+        }
+        let pair_mismatched = run_coordination_pair(CoordinationRunConfig {
+            mode: ExecutionMode::Warm,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 1,
+            live_events: 1,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_mismatched),
+            debug_output_dir: None,
+        })
+        .expect("pair should run");
+        assert_eq!(pair_mismatched.unified.hybrid_result_count, 0);
+        assert_eq!(pair_mismatched.decomposed.hybrid_result_count, 0);
+    }
+
+    #[test]
+    fn test_sustained_expected_completed_windows_formula() {
+        // window_size=120s, slide=60s, duration=240s
+        let duration = 240;
+        let window_size = 120;
+        let slide = 60;
+        let first_start = window_size - slide - 1;
+        let last_event = duration - 1;
+        let close_ts = last_event + 20;
+        let expected = if close_ts >= first_start {
+            1 + (close_ts - first_start) / slide
+        } else {
+            0
+        };
+        assert_eq!(expected, 4);
+    }
+
+    #[test]
+    fn test_sustained_wall_clock_config_helpers() {
+        assert!((sustained_event_interval_ms(4) - 250.0).abs() < f64::EPSILON);
+        assert_eq!(sustained_expected_wall_clock_duration_ms(20), 20_000);
+    }
+
+    #[test]
+    fn test_sustained_hybrid_dependency_and_equivalence() {
+        let metadata = test_metadata();
+        let adapter = OxigraphExternalAdapter::new();
+
+        // 1. Janus and decomposed baseline match per-window result hashes on a tiny workload
+        let workload_1_1 =
+            prepare_sustained_workload(100, 240, 1, 120, 60).expect("workload should build");
+        let pair_1_1 = run_sustained_pair(SustainedRunConfig {
+            mode: ExecutionMode::Warm,
+            time_mode: TimeMode::Virtual,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 100,
+            live_duration_seconds: 240,
+            event_rate_hz: 1,
+            event_interval_ms: sustained_event_interval_ms(1),
+            expected_wall_clock_duration_ms: sustained_expected_wall_clock_duration_ms(240),
+            window_size_seconds: 120,
+            window_slide_seconds: 60,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_1_1),
+            debug_output_dir: None,
+        })
+        .expect("sustained pair should run");
+
+        assert_eq!(pair_1_1.unified.expected_completed_windows, 2);
+        assert_eq!(pair_1_1.unified.completed_windows_total, 4);
+        assert_eq!(pair_1_1.unified.completed_windows_in_horizon, 2);
+        assert_eq!(pair_1_1.unified.flush_windows, 2);
+        assert_eq!(pair_1_1.unified.time_mode, "virtual");
+        assert!(pair_1_1.unified.uses_virtual_event_time);
+        assert!((pair_1_1.unified.event_interval_ms - 1000.0).abs() < f64::EPSILON);
+        assert_eq!(pair_1_1.unified.expected_wall_clock_duration_ms, 240_000);
+        assert_eq!(pair_1_1.decomposed.completed_windows_total, 4);
+        assert_eq!(pair_1_1.decomposed.completed_windows_in_horizon, 2);
+        assert_eq!(pair_1_1.decomposed.flush_windows, 2);
+        assert!(pair_1_1.decomposed.uses_virtual_event_time);
+        assert_eq!(pair_1_1.unified.equivalent_to_baseline, Some(true));
+        assert!(pair_1_1.unified.hybrid_result_count_total > 0);
+
+        // 2. Removing historical input yields zero hybrid results
+        let workload_no_hist =
+            prepare_sustained_workload(0, 240, 1, 120, 60).expect("workload should build");
+        let pair_no_hist = run_sustained_pair(SustainedRunConfig {
+            mode: ExecutionMode::Warm,
+            time_mode: TimeMode::Virtual,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 0,
+            live_duration_seconds: 240,
+            event_rate_hz: 1,
+            event_interval_ms: sustained_event_interval_ms(1),
+            expected_wall_clock_duration_ms: sustained_expected_wall_clock_duration_ms(240),
+            window_size_seconds: 120,
+            window_slide_seconds: 60,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_no_hist),
+            debug_output_dir: None,
+        })
+        .expect("sustained pair should run");
+        assert_eq!(pair_no_hist.unified.hybrid_result_count_total, 0);
+        assert_eq!(pair_no_hist.decomposed.hybrid_result_count_total, 0);
+
+        // 3. Removing live input yields zero hybrid results
+        let workload_no_live =
+            prepare_sustained_workload(100, 0, 1, 120, 60).expect("workload should build");
+        let pair_no_live = run_sustained_pair(SustainedRunConfig {
+            mode: ExecutionMode::Warm,
+            time_mode: TimeMode::Virtual,
+            run_index: 0,
+            is_warmup: false,
+            historical_events: 100,
+            live_duration_seconds: 0,
+            event_rate_hz: 1,
+            event_interval_ms: sustained_event_interval_ms(1),
+            expected_wall_clock_duration_ms: sustained_expected_wall_clock_duration_ms(0),
+            window_size_seconds: 120,
+            window_slide_seconds: 60,
+            metadata: &metadata,
+            adapter: &adapter,
+            warm_workload: Some(&workload_no_live),
+            debug_output_dir: None,
+        })
+        .expect("sustained pair should run");
+        assert_eq!(pair_no_live.unified.hybrid_result_count_total, 0);
+        assert_eq!(pair_no_live.decomposed.hybrid_result_count_total, 0);
+    }
+}
diff --git a/src/paper_bench/historical_range.rs b/src/paper_bench/historical_range.rs
new file mode 100644
index 0000000..41e52ea
--- /dev/null
+++ b/src/paper_bench/historical_range.rs
@@ -0,0 +1,1070 @@
+use crate::core::RDFEvent;
+use crate::extensions::query_options::build_evaluator;
+use crate::storage::segmented_storage::StreamingSegmentedStorage;
+use crate::storage::util::StreamingConfig;
+use clap::ValueEnum;
+use oxigraph::model::{GraphName, Literal, NamedNode, Quad, Term};
+use oxigraph::sparql::QueryResults;
+use oxigraph::store::Store;
+use plotters::prelude::*;
+use serde::Serialize;
+use sha2::{Digest, Sha256};
+use std::cmp::Ordering;
+use std::collections::HashMap;
+use std::error::Error;
+use std::fs::{self, File};
+use std::io::Write;
+use std::path::{Path, PathBuf};
+use std::sync::atomic::{AtomicU64, Ordering as AtomicOrdering};
+use std::sync::Arc;
+use std::time::Instant;
+
+type BoxError = Box<dyn Error>;
+
+pub const DEFAULT_DATASET_SIZES: [usize; 4] = [10_000, 50_000, 100_000, 500_000];
+pub const DEFAULT_FIXED_RANGE_SECONDS: u64 = 60;
+pub const RESULT_MARKDOWN_FILE: &str = "h2_range_comparison_results.md";
+pub const FIXED_60S_PLOT_FILE: &str = "h2_fixed_60s_janus_vs_oxigraph.png";
+pub const FULL_HISTORY_PLOT_FILE: &str = "h2_full_history_janus_vs_oxigraph.png";
+
+const BASE_TIMESTAMP_MS: u64 = 1_720_000_000_000;
+const TIMESTAMP_STEP_MS: u64 = 10;
+const TIMESTAMP_PREDICATE: &str = "http://example.org/schema/timestamp";
+const TIMESTAMP_DATATYPE: &str = "http://www.w3.org/2001/XMLSchema#long";
+
+static CONFIG_COUNTER: AtomicU64 = AtomicU64::new(0);
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, ValueEnum)]
+pub enum HistoricalRangeMode {
+    Warm,
+    Cold,
+}
+
+impl HistoricalRangeMode {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Warm => "warm",
+            Self::Cold => "cold",
+        }
+    }
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Hash, ValueEnum)]
+pub enum HistoricalRangeQueryCaseArg {
+    #[value(name = "fixed_60s")]
+    Fixed60s,
+    #[value(name = "full_history")]
+    FullHistory,
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Hash)]
+pub enum HistoricalRangeQueryCase {
+    Fixed60sRange,
+    FullHistoryRange,
+}
+
+impl HistoricalRangeQueryCase {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Fixed60sRange => "fixed_60s_range",
+            Self::FullHistoryRange => "full_history_range",
+        }
+    }
+
+    pub fn from_arg(value: HistoricalRangeQueryCaseArg) -> Self {
+        match value {
+            HistoricalRangeQueryCaseArg::Fixed60s => Self::Fixed60sRange,
+            HistoricalRangeQueryCaseArg::FullHistory => Self::FullHistoryRange,
+        }
+    }
+
+    fn janus_row_label(self) -> &'static str {
+        match self {
+            Self::Fixed60sRange => "Janus fixed 60s",
+            Self::FullHistoryRange => "Janus full history",
+        }
+    }
+
+    fn oxigraph_row_label(self) -> &'static str {
+        match self {
+            Self::Fixed60sRange => "Oxigraph fixed 60s FILTER",
+            Self::FullHistoryRange => "Oxigraph full history FILTER",
+        }
+    }
+
+    fn takeaway(self) -> &'static str {
+        match self {
+            Self::Fixed60sRange => "Bounded timestamp lookup",
+            Self::FullHistoryRange => "Full historical read",
+        }
+    }
+}
+
+#[derive(Clone, Debug)]
+pub struct HistoricalRangeComparisonConfig {
+    pub runs: usize,
+    pub warmup_runs: usize,
+    pub dataset_sizes: Vec<usize>,
+    pub query_cases: Vec<HistoricalRangeQueryCase>,
+    pub fixed_range_seconds: u64,
+    pub mode: HistoricalRangeMode,
+    pub debug_equivalence: bool,
+    pub output_dir: PathBuf,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct HistoricalRangeRawRow {
+    pub system: String,
+    pub dataset_size_quads: usize,
+    pub event_count: usize,
+    pub query_case: String,
+    pub range_start_ms: u64,
+    pub range_end_ms: u64,
+    pub range_width_ms: u64,
+    pub result_count: usize,
+    pub result_hash: String,
+    pub equivalent_to_baseline: bool,
+    pub latency_ms: f64,
+    pub run_id: usize,
+    pub is_warmup: bool,
+    pub mode: String,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct HistoricalRangeSummaryRow {
+    pub dataset_size_quads: usize,
+    pub query_case: String,
+    pub range_width_ms: u64,
+    pub result_count: usize,
+    pub janus_p50_ms: f64,
+    pub oxigraph_p50_ms: f64,
+    pub janus_p95_ms: f64,
+    pub oxigraph_p95_ms: f64,
+    pub janus_avg_ms: f64,
+    pub oxigraph_avg_ms: f64,
+    pub ratio_oxigraph_over_janus: f64,
+    pub equivalent: bool,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct HistoricalRangeRunOutcome {
+    pub dataset_size_quads: usize,
+    pub event_count: usize,
+    pub query_case: String,
+    pub range_start_ms: u64,
+    pub range_end_ms: u64,
+    pub range_width_ms: u64,
+    pub janus_result_count: usize,
+    pub oxigraph_result_count: usize,
+    pub janus_result_hash: String,
+    pub oxigraph_result_hash: String,
+    pub equivalent: bool,
+    pub run_id: usize,
+    pub is_warmup: bool,
+}
+
+#[derive(Clone, Debug)]
+pub struct HistoricalRangeComparisonOutcome {
+    pub changed_output_files: Vec<PathBuf>,
+    pub raw_rows: Vec<HistoricalRangeRawRow>,
+    pub summary_rows: Vec<HistoricalRangeSummaryRow>,
+    pub run_outcomes: Vec<HistoricalRangeRunOutcome>,
+}
+
+#[derive(Clone)]
+struct PreparedDataset {
+    dataset_size_quads: usize,
+    event_count: usize,
+    timestamp_min: u64,
+    timestamp_max: u64,
+    janus_storage: Arc<StreamingSegmentedStorage>,
+    oxigraph_store: Store,
+}
+
+#[derive(Clone, Debug)]
+struct RangeDefinition {
+    start_ms: u64,
+    end_ms_exclusive: u64,
+}
+
+struct RunExecutionContext<'a> {
+    run_id: usize,
+    is_warmup: bool,
+    fixed_range_seconds: u64,
+    mode: HistoricalRangeMode,
+    debug_equivalence: bool,
+    output_dir: &'a Path,
+}
+
+#[derive(Clone, Debug, Serialize)]
+struct CanonicalResultRow {
+    subject: String,
+    predicate: String,
+    object: String,
+    graph: String,
+    timestamp_ms: u64,
+}
+
+#[derive(Clone, Debug, Serialize)]
+struct EquivalenceReport {
+    dataset_size_quads: usize,
+    event_count: usize,
+    query_case: String,
+    range_start_ms: u64,
+    range_end_ms: u64,
+    range_width_ms: u64,
+    janus_result_count: usize,
+    oxigraph_result_count: usize,
+    janus_result_hash: String,
+    oxigraph_result_hash: String,
+    equivalent: bool,
+}
+
+struct EquivalenceDebugContext<'a> {
+    output_dir: &'a Path,
+    dataset: &'a PreparedDataset,
+    query_case: HistoricalRangeQueryCase,
+    run_id: usize,
+    is_warmup: bool,
+    range: &'a RangeDefinition,
+    janus_rows: &'a [CanonicalResultRow],
+    oxigraph_rows: &'a [CanonicalResultRow],
+    janus_hash: &'a str,
+    oxigraph_hash: &'a str,
+}
+
+pub fn run_historical_range_comparison(
+    config: &HistoricalRangeComparisonConfig,
+) -> Result<HistoricalRangeComparisonOutcome, BoxError> {
+    ensure_output_dir(&config.output_dir)?;
+    ensure_output_dir(Path::new("target/paper_benchmarks"))?;
+
+    let mut raw_rows = Vec::new();
+    let mut run_outcomes = Vec::new();
+
+    for &dataset_size in &config.dataset_sizes {
+        let warm_dataset = if config.mode == HistoricalRangeMode::Warm {
+            Some(prepare_dataset(dataset_size)?)
+        } else {
+            None
+        };
+
+        for &query_case in &config.query_cases {
+            for run_id in 0..config.warmup_runs {
+                let dataset = if let Some(dataset) = &warm_dataset {
+                    dataset.clone()
+                } else {
+                    prepare_dataset(dataset_size)?
+                };
+                let run = execute_query_case(
+                    &dataset,
+                    query_case,
+                    &RunExecutionContext {
+                        run_id,
+                        is_warmup: true,
+                        fixed_range_seconds: config.fixed_range_seconds,
+                        mode: config.mode,
+                        debug_equivalence: config.debug_equivalence,
+                        output_dir: &config.output_dir,
+                    },
+                )?;
+                raw_rows.extend(run.0);
+                run_outcomes.push(run.1);
+            }
+
+            for run_id in 0..config.runs {
+                let dataset = if let Some(dataset) = &warm_dataset {
+                    dataset.clone()
+                } else {
+                    prepare_dataset(dataset_size)?
+                };
+                let run = execute_query_case(
+                    &dataset,
+                    query_case,
+                    &RunExecutionContext {
+                        run_id,
+                        is_warmup: false,
+                        fixed_range_seconds: config.fixed_range_seconds,
+                        mode: config.mode,
+                        debug_equivalence: config.debug_equivalence,
+                        output_dir: &config.output_dir,
+                    },
+                )?;
+                raw_rows.extend(run.0);
+                run_outcomes.push(run.1);
+            }
+        }
+    }
+
+    let summary_rows = summarize_rows(&raw_rows);
+    let raw_jsonl = config.output_dir.join("paper_historical_range_comparison.raw.jsonl");
+    let summary_csv = config.output_dir.join("paper_historical_range_comparison.summary.csv");
+    let markdown_path = config.output_dir.join(RESULT_MARKDOWN_FILE);
+    let fixed_plot_path = config.output_dir.join(FIXED_60S_PLOT_FILE);
+    let full_plot_path = config.output_dir.join(FULL_HISTORY_PLOT_FILE);
+
+    write_jsonl(&raw_jsonl, &raw_rows)?;
+    write_summary_csv(&summary_csv, &summary_rows)?;
+    write_markdown(&markdown_path, &summary_rows)?;
+    write_plot(
+        &fixed_plot_path,
+        &summary_rows,
+        HistoricalRangeQueryCase::Fixed60sRange,
+        "H2 Fixed 60s Janus vs Oxigraph",
+    )?;
+    write_plot(
+        &full_plot_path,
+        &summary_rows,
+        HistoricalRangeQueryCase::FullHistoryRange,
+        "H2 Full History Janus vs Oxigraph",
+    )?;
+
+    Ok(HistoricalRangeComparisonOutcome {
+        changed_output_files: vec![
+            raw_jsonl,
+            summary_csv,
+            markdown_path,
+            fixed_plot_path,
+            full_plot_path,
+        ],
+        raw_rows,
+        summary_rows,
+        run_outcomes,
+    })
+}
+
+fn execute_query_case(
+    dataset: &PreparedDataset,
+    query_case: HistoricalRangeQueryCase,
+    context: &RunExecutionContext<'_>,
+) -> Result<(Vec<HistoricalRangeRawRow>, HistoricalRangeRunOutcome), BoxError> {
+    let range = range_for_case(dataset, query_case, context.fixed_range_seconds)?;
+    let query_text = oxigraph_timestamp_filter_query(range.start_ms, range.end_ms_exclusive);
+
+    let janus_started = Instant::now();
+    let janus_results =
+        historical_range(&dataset.janus_storage, range.start_ms, range.end_ms_exclusive)?;
+    let janus_latency_ms = janus_started.elapsed().as_secs_f64() * 1_000.0;
+    let janus_canonical = canonicalize_janus_results(&janus_results);
+    let janus_hash = result_hash(&janus_canonical)?;
+
+    let oxigraph_started = Instant::now();
+    let oxigraph_results = execute_oxigraph_range_query(&dataset.oxigraph_store, &query_text)?;
+    let oxigraph_latency_ms = oxigraph_started.elapsed().as_secs_f64() * 1_000.0;
+    let oxigraph_hash = result_hash(&oxigraph_results)?;
+
+    let equivalent = janus_canonical.len() == oxigraph_results.len() && janus_hash == oxigraph_hash;
+
+    if context.debug_equivalence {
+        write_query_debug_artifact(
+            context.output_dir,
+            dataset.dataset_size_quads,
+            query_case,
+            context.run_id,
+            context.is_warmup,
+            &query_text,
+        )?;
+    }
+
+    if !equivalent && context.debug_equivalence {
+        write_equivalence_debug_artifacts(&EquivalenceDebugContext {
+            output_dir: context.output_dir,
+            dataset,
+            query_case,
+            run_id: context.run_id,
+            is_warmup: context.is_warmup,
+            range: &range,
+            janus_rows: &janus_canonical,
+            oxigraph_rows: &oxigraph_results,
+            janus_hash: &janus_hash,
+            oxigraph_hash: &oxigraph_hash,
+        })?;
+    }
+
+    let range_width_ms = range.end_ms_exclusive.saturating_sub(range.start_ms);
+    let janus_raw = HistoricalRangeRawRow {
+        system: "janus".to_string(),
+        dataset_size_quads: dataset.dataset_size_quads,
+        event_count: dataset.event_count,
+        query_case: query_case.as_str().to_string(),
+        range_start_ms: range.start_ms,
+        range_end_ms: range.end_ms_exclusive,
+        range_width_ms,
+        result_count: janus_canonical.len(),
+        result_hash: janus_hash.clone(),
+        equivalent_to_baseline: equivalent,
+        latency_ms: janus_latency_ms,
+        run_id: context.run_id,
+        is_warmup: context.is_warmup,
+        mode: context.mode.as_str().to_string(),
+    };
+    let oxigraph_raw = HistoricalRangeRawRow {
+        system: "oxigraph".to_string(),
+        dataset_size_quads: dataset.dataset_size_quads,
+        event_count: dataset.event_count,
+        query_case: query_case.as_str().to_string(),
+        range_start_ms: range.start_ms,
+        range_end_ms: range.end_ms_exclusive,
+        range_width_ms,
+        result_count: oxigraph_results.len(),
+        result_hash: oxigraph_hash.clone(),
+        equivalent_to_baseline: equivalent,
+        latency_ms: oxigraph_latency_ms,
+        run_id: context.run_id,
+        is_warmup: context.is_warmup,
+        mode: context.mode.as_str().to_string(),
+    };
+    let outcome = HistoricalRangeRunOutcome {
+        dataset_size_quads: dataset.dataset_size_quads,
+        event_count: dataset.event_count,
+        query_case: query_case.as_str().to_string(),
+        range_start_ms: range.start_ms,
+        range_end_ms: range.end_ms_exclusive,
+        range_width_ms,
+        janus_result_count: janus_canonical.len(),
+        oxigraph_result_count: oxigraph_results.len(),
+        janus_result_hash: janus_hash,
+        oxigraph_result_hash: oxigraph_hash,
+        equivalent,
+        run_id: context.run_id,
+        is_warmup: context.is_warmup,
+    };
+    Ok((vec![janus_raw, oxigraph_raw], outcome))
+}
+
+fn prepare_dataset(dataset_size_quads: usize) -> Result<PreparedDataset, BoxError> {
+    let janus_storage = Arc::new(StreamingSegmentedStorage::new(unique_config("paper_h2_range"))?);
+    let oxigraph_store = Store::new()?;
+    let timestamp_predicate = NamedNode::new(TIMESTAMP_PREDICATE)?;
+    let timestamp_datatype = NamedNode::new(TIMESTAMP_DATATYPE)?;
+    let timestamp_min = BASE_TIMESTAMP_MS;
+    let mut timestamp_max = BASE_TIMESTAMP_MS;
+
+    for index in 0..dataset_size_quads {
+        let timestamp_ms = BASE_TIMESTAMP_MS + (index as u64 * TIMESTAMP_STEP_MS);
+        timestamp_max = timestamp_ms;
+        let event = RDFEvent::new(
+            timestamp_ms,
+            &format!("http://example.org/event/{index:08}"),
+            TIMESTAMP_PREDICATE,
+            &typed_timestamp_literal(timestamp_ms),
+            "",
+        );
+        janus_storage.write_rdf_event(event.clone())?;
+        oxigraph_store.insert(&Quad::new(
+            NamedNode::new(event.subject.as_str())?,
+            timestamp_predicate.clone(),
+            Literal::new_typed_literal(timestamp_ms.to_string(), timestamp_datatype.clone()),
+            GraphName::DefaultGraph,
+        ))?;
+    }
+    janus_storage.flush()?;
+
+    Ok(PreparedDataset {
+        dataset_size_quads,
+        event_count: dataset_size_quads,
+        timestamp_min,
+        timestamp_max,
+        janus_storage,
+        oxigraph_store,
+    })
+}
+
+fn range_for_case(
+    dataset: &PreparedDataset,
+    query_case: HistoricalRangeQueryCase,
+    fixed_range_seconds: u64,
+) -> Result<RangeDefinition, BoxError> {
+    let start_ms = dataset.timestamp_min;
+    let end_ms_exclusive = match query_case {
+        HistoricalRangeQueryCase::Fixed60sRange => start_ms
+            .checked_add(fixed_range_seconds.saturating_mul(1_000))
+            .ok_or("fixed range end overflowed u64")?,
+        HistoricalRangeQueryCase::FullHistoryRange => dataset
+            .timestamp_max
+            .checked_add(1)
+            .ok_or("full history range end overflowed u64")?,
+    };
+    Ok(RangeDefinition { start_ms, end_ms_exclusive })
+}
+
+fn historical_range(
+    storage: &Arc<StreamingSegmentedStorage>,
+    start_ms: u64,
+    end_ms_exclusive: u64,
+) -> Result<Vec<RDFEvent>, BoxError> {
+    if end_ms_exclusive <= start_ms {
+        return Ok(Vec::new());
+    }
+    let end_ms_inclusive = end_ms_exclusive.saturating_sub(1);
+    Ok(storage.query_rdf(start_ms, end_ms_inclusive)?)
+}
+
+fn execute_oxigraph_range_query(
+    store: &Store,
+    query_text: &str,
+) -> Result<Vec<CanonicalResultRow>, BoxError> {
+    let evaluator = build_evaluator();
+    let parsed_query = evaluator.parse_query(query_text)?;
+    let results = parsed_query.on_store(store).execute()?;
+    let mut rows = Vec::new();
+
+    if let QueryResults::Solutions(solutions) = results {
+        for solution in solutions {
+            let solution = solution?;
+            let event_term = solution.get("event").ok_or("missing ?event binding")?;
+            let timestamp_term = solution.get("t").ok_or("missing ?t binding")?;
+
+            let subject = match event_term {
+                Term::NamedNode(node) => node.as_str().to_string(),
+                other => return Err(format!("expected NamedNode for ?event, got {other}").into()),
+            };
+            let timestamp_ms = match timestamp_term {
+                Term::Literal(literal) => literal.value().parse::<u64>()?,
+                other => return Err(format!("expected Literal for ?t, got {other}").into()),
+            };
+
+            rows.push(CanonicalResultRow {
+                subject,
+                predicate: TIMESTAMP_PREDICATE.to_string(),
+                object: typed_timestamp_literal(timestamp_ms),
+                graph: String::new(),
+                timestamp_ms,
+            });
+        }
+    }
+
+    rows.sort_by(canonical_row_cmp);
+    Ok(rows)
+}
+
+fn oxigraph_timestamp_filter_query(range_start_ms: u64, range_end_ms: u64) -> String {
+    format!(
+        "PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\n\
+SELECT ?event ?t\n\
+WHERE {{\n\
+  ?event <{TIMESTAMP_PREDICATE}> ?t .\n\
+  FILTER (?t >= \"{range_start_ms}\"^^xsd:long && ?t < \"{range_end_ms}\"^^xsd:long)\n\
+}}\n"
+    )
+}
+
+fn canonicalize_janus_results(results: &[RDFEvent]) -> Vec<CanonicalResultRow> {
+    let mut rows = results
+        .iter()
+        .map(|event| CanonicalResultRow {
+            subject: event.subject.clone(),
+            predicate: event.predicate.clone(),
+            object: typed_timestamp_literal(event.timestamp),
+            graph: event.graph.clone(),
+            timestamp_ms: event.timestamp,
+        })
+        .collect::<Vec<_>>();
+    rows.sort_by(canonical_row_cmp);
+    rows
+}
+
+fn canonical_row_cmp(left: &CanonicalResultRow, right: &CanonicalResultRow) -> Ordering {
+    left.timestamp_ms
+        .cmp(&right.timestamp_ms)
+        .then_with(|| left.subject.cmp(&right.subject))
+        .then_with(|| left.predicate.cmp(&right.predicate))
+        .then_with(|| left.object.cmp(&right.object))
+        .then_with(|| left.graph.cmp(&right.graph))
+}
+
+fn result_hash(rows: &[CanonicalResultRow]) -> Result<String, BoxError> {
+    let payload = serde_json::to_vec(rows)?;
+    Ok(format!("{:x}", Sha256::digest(payload)))
+}
+
+fn typed_timestamp_literal(timestamp_ms: u64) -> String {
+    format!("\"{timestamp_ms}\"^^<{TIMESTAMP_DATATYPE}>")
+}
+
+fn summarize_rows(rows: &[HistoricalRangeRawRow]) -> Vec<HistoricalRangeSummaryRow> {
+    let mut janus_rows = HashMap::<(usize, String), Vec<&HistoricalRangeRawRow>>::new();
+    let mut oxigraph_rows = HashMap::<(usize, String), Vec<&HistoricalRangeRawRow>>::new();
+
+    for row in rows.iter().filter(|row| !row.is_warmup) {
+        let key = (row.dataset_size_quads, row.query_case.clone());
+        if row.system == "janus" {
+            janus_rows.entry(key).or_default().push(row);
+        } else if row.system == "oxigraph" {
+            oxigraph_rows.entry(key).or_default().push(row);
+        }
+    }
+
+    let mut keys = janus_rows.keys().cloned().collect::<Vec<_>>();
+    keys.sort_by(|left, right| left.0.cmp(&right.0).then_with(|| left.1.cmp(&right.1)));
+
+    keys.into_iter()
+        .filter_map(|key| {
+            let janus = janus_rows.get(&key)?;
+            let oxigraph = oxigraph_rows.get(&key)?;
+            let janus_latencies = janus.iter().map(|row| row.latency_ms).collect::<Vec<_>>();
+            let oxigraph_latencies = oxigraph.iter().map(|row| row.latency_ms).collect::<Vec<_>>();
+            let janus_p50 = percentile(&janus_latencies, 50.0);
+            let oxigraph_p50 = percentile(&oxigraph_latencies, 50.0);
+            Some(HistoricalRangeSummaryRow {
+                dataset_size_quads: key.0,
+                query_case: key.1,
+                range_width_ms: janus.first().map_or(0, |row| row.range_width_ms),
+                result_count: janus.first().map_or(0, |row| row.result_count),
+                janus_p50_ms: janus_p50,
+                oxigraph_p50_ms: oxigraph_p50,
+                janus_p95_ms: percentile(&janus_latencies, 95.0),
+                oxigraph_p95_ms: percentile(&oxigraph_latencies, 95.0),
+                janus_avg_ms: mean(&janus_latencies),
+                oxigraph_avg_ms: mean(&oxigraph_latencies),
+                ratio_oxigraph_over_janus: if janus_p50 > 0.0 {
+                    oxigraph_p50 / janus_p50
+                } else {
+                    0.0
+                },
+                equivalent: janus.iter().all(|row| row.equivalent_to_baseline)
+                    && oxigraph.iter().all(|row| row.equivalent_to_baseline),
+            })
+        })
+        .collect()
+}
+
+fn write_summary_csv(path: &Path, rows: &[HistoricalRangeSummaryRow]) -> Result<(), BoxError> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "dataset_size_quads,query_case,range_width_ms,result_count,janus_p50_ms,oxigraph_p50_ms,janus_p95_ms,oxigraph_p95_ms,janus_avg_ms,oxigraph_avg_ms,ratio_oxigraph_over_janus,equivalent"
+    )?;
+    for row in rows {
+        writeln!(
+            file,
+            "{},{},{},{},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{:.3},{}",
+            row.dataset_size_quads,
+            row.query_case,
+            row.range_width_ms,
+            row.result_count,
+            row.janus_p50_ms,
+            row.oxigraph_p50_ms,
+            row.janus_p95_ms,
+            row.oxigraph_p95_ms,
+            row.janus_avg_ms,
+            row.oxigraph_avg_ms,
+            row.ratio_oxigraph_over_janus,
+            row.equivalent
+        )?;
+    }
+    Ok(())
+}
+
+fn write_markdown(path: &Path, rows: &[HistoricalRangeSummaryRow]) -> Result<(), BoxError> {
+    let mut file = File::create(path)?;
+    let sizes = DEFAULT_DATASET_SIZES;
+
+    writeln!(file, "# H2 Historical Timestamp Range Comparison")?;
+    writeln!(file)?;
+    writeln!(file, "## Query")?;
+    writeln!(file)?;
+    writeln!(file, "Both systems answer the same timestamp range query:")?;
+    writeln!(file)?;
+    writeln!(file, "timestamp >= X")?;
+    writeln!(file, "timestamp < Y")?;
+    writeln!(file)?;
+    writeln!(
+        file,
+        "Janus executes this as a historical range lookup over its event-log structure."
+    )?;
+    writeln!(file)?;
+    writeln!(file, "Oxigraph executes this as SPARQL over the same RDF quads:")?;
+    writeln!(file)?;
+    writeln!(file, "SELECT ?event ?t")?;
+    writeln!(file, "WHERE {{")?;
+    writeln!(file, "  ?event <{TIMESTAMP_PREDICATE}> ?t .")?;
+    writeln!(file, "  FILTER (?t >= X && ?t < Y)")?;
+    writeln!(file, "}}")?;
+    writeln!(file)?;
+    writeln!(file, "## Result")?;
+    writeln!(file)?;
+    writeln!(
+        file,
+        "| Query Case | 10k quads | 50k quads | 100k quads | 500k quads | Takeaway |"
+    )?;
+    writeln!(file, "| --- | ---: | ---: | ---: | ---: | --- |")?;
+
+    for query_case in [
+        HistoricalRangeQueryCase::Fixed60sRange,
+        HistoricalRangeQueryCase::FullHistoryRange,
+    ] {
+        let janus_cells = sizes
+            .iter()
+            .map(|size| metric_cell(rows, *size, query_case, "janus"))
+            .collect::<Vec<_>>();
+        writeln!(
+            file,
+            "| {} | {} | {} | {} | {} | {} |",
+            query_case.janus_row_label(),
+            janus_cells[0],
+            janus_cells[1],
+            janus_cells[2],
+            janus_cells[3],
+            query_case.takeaway()
+        )?;
+
+        let oxigraph_cells = sizes
+            .iter()
+            .map(|size| metric_cell(rows, *size, query_case, "oxigraph"))
+            .collect::<Vec<_>>();
+        writeln!(
+            file,
+            "| {} | {} | {} | {} | {} | {} |",
+            query_case.oxigraph_row_label(),
+            oxigraph_cells[0],
+            oxigraph_cells[1],
+            oxigraph_cells[2],
+            oxigraph_cells[3],
+            match query_case {
+                HistoricalRangeQueryCase::Fixed60sRange => "SPARQL timestamp filter",
+                HistoricalRangeQueryCase::FullHistoryRange => "Full timestamp-filter scan",
+            }
+        )?;
+    }
+
+    writeln!(file)?;
+    writeln!(file, "| Query Case | 10k | 50k | 100k | 500k |")?;
+    writeln!(file, "| --- | --- | --- | --- | --- |")?;
+    for query_case in [
+        HistoricalRangeQueryCase::Fixed60sRange,
+        HistoricalRangeQueryCase::FullHistoryRange,
+    ] {
+        let cells = sizes
+            .iter()
+            .map(|size| equivalence_cell(rows, *size, query_case))
+            .collect::<Vec<_>>();
+        writeln!(
+            file,
+            "| {} | {} | {} | {} | {} |",
+            query_case.as_str(),
+            cells[0],
+            cells[1],
+            cells[2],
+            cells[3]
+        )?;
+    }
+
+    writeln!(file)?;
+    writeln!(file, "## Interpretation")?;
+    writeln!(file)?;
+    writeln!(
+        file,
+        "- fixed_60s_range tests bounded lookup over a 60-second historical interval"
+    )?;
+    writeln!(file, "- full_history_range tests reading all historical data")?;
+    writeln!(
+        file,
+        "- this directly compares Janus historical retrieval with Oxigraph SPARQL timestamp FILTER over the same RDF event log data"
+    )?;
+    Ok(())
+}
+
+fn metric_cell(
+    rows: &[HistoricalRangeSummaryRow],
+    dataset_size_quads: usize,
+    query_case: HistoricalRangeQueryCase,
+    system: &str,
+) -> String {
+    let Some(row) = rows.iter().find(|row| {
+        row.dataset_size_quads == dataset_size_quads && row.query_case == query_case.as_str()
+    }) else {
+        return String::new();
+    };
+    let value = if system == "janus" {
+        row.janus_p50_ms
+    } else {
+        row.oxigraph_p50_ms
+    };
+    format!("{value:.3}")
+}
+
+fn equivalence_cell(
+    rows: &[HistoricalRangeSummaryRow],
+    dataset_size_quads: usize,
+    query_case: HistoricalRangeQueryCase,
+) -> &'static str {
+    rows.iter()
+        .find(|row| {
+            row.dataset_size_quads == dataset_size_quads && row.query_case == query_case.as_str()
+        })
+        .map_or("no", |row| if row.equivalent { "yes" } else { "no" })
+}
+
+fn write_plot(
+    path: &Path,
+    rows: &[HistoricalRangeSummaryRow],
+    query_case: HistoricalRangeQueryCase,
+    caption: &str,
+) -> Result<(), BoxError> {
+    let case_rows = rows
+        .iter()
+        .filter(|row| row.query_case == query_case.as_str())
+        .cloned()
+        .collect::<Vec<_>>();
+    if case_rows.is_empty() {
+        return Ok(());
+    }
+
+    let root = BitMapBackend::new(path, (960, 540)).into_drawing_area();
+    root.fill(&WHITE)?;
+
+    let y_max = case_rows
+        .iter()
+        .flat_map(|row| [row.janus_p50_ms, row.oxigraph_p50_ms])
+        .fold(0.0_f64, f64::max)
+        .max(1.0)
+        * 1.1;
+
+    let x_upper = i32::try_from(case_rows.len()).map_err(|_| "too many plot points for i32")?;
+    let x_range = 0_i32..x_upper;
+    let mut chart = ChartBuilder::on(&root)
+        .caption(caption, ("sans-serif", 24))
+        .margin(20)
+        .x_label_area_size(40)
+        .y_label_area_size(60)
+        .build_cartesian_2d(x_range, 0.0_f64..y_max)?;
+
+    let labels = case_rows
+        .iter()
+        .map(|row| dataset_label(row.dataset_size_quads))
+        .collect::<Vec<_>>();
+
+    chart
+        .configure_mesh()
+        .x_desc("dataset size")
+        .y_desc("p50 latency ms")
+        .x_labels(case_rows.len())
+        .x_label_formatter(&|value| {
+            usize::try_from(*value)
+                .ok()
+                .and_then(|index| labels.get(index).cloned())
+                .unwrap_or_default()
+        })
+        .draw()?;
+
+    let janus_points = case_rows
+        .iter()
+        .enumerate()
+        .map(|(index, row)| {
+            Ok((
+                i32::try_from(index).map_err(|_| "too many plot points for i32")?,
+                row.janus_p50_ms,
+            ))
+        })
+        .collect::<Result<Vec<_>, BoxError>>()?;
+    let oxigraph_points = case_rows
+        .iter()
+        .enumerate()
+        .map(|(index, row)| {
+            Ok((
+                i32::try_from(index).map_err(|_| "too many plot points for i32")?,
+                row.oxigraph_p50_ms,
+            ))
+        })
+        .collect::<Result<Vec<_>, BoxError>>()?;
+
+    chart
+        .draw_series(LineSeries::new(janus_points.clone(), &BLUE))?
+        .label("Janus")
+        .legend(|(x, y)| PathElement::new(vec![(x, y), (x + 20, y)], BLUE));
+    chart
+        .draw_series(janus_points.into_iter().map(|point| Circle::new(point, 4, BLUE.filled())))?;
+
+    chart
+        .draw_series(LineSeries::new(oxigraph_points.clone(), &RED))?
+        .label("Oxigraph")
+        .legend(|(x, y)| PathElement::new(vec![(x, y), (x + 20, y)], RED));
+    chart.draw_series(
+        oxigraph_points
+            .into_iter()
+            .map(|point| TriangleMarker::new(point, 6, RED.filled())),
+    )?;
+
+    chart
+        .configure_series_labels()
+        .background_style(WHITE.mix(0.8))
+        .border_style(BLACK)
+        .draw()?;
+    root.present()?;
+    Ok(())
+}
+
+fn write_query_debug_artifact(
+    output_dir: &Path,
+    dataset_size_quads: usize,
+    query_case: HistoricalRangeQueryCase,
+    run_id: usize,
+    is_warmup: bool,
+    query_text: &str,
+) -> Result<(), BoxError> {
+    let run_dir = debug_run_dir(output_dir, dataset_size_quads, query_case, run_id, is_warmup);
+    ensure_output_dir(&run_dir)?;
+    fs::write(run_dir.join("oxigraph_timestamp_filter_query.rq"), query_text)?;
+    Ok(())
+}
+
+fn write_equivalence_debug_artifacts(
+    context: &EquivalenceDebugContext<'_>,
+) -> Result<(), BoxError> {
+    let run_dir = debug_run_dir(
+        context.output_dir,
+        context.dataset.dataset_size_quads,
+        context.query_case,
+        context.run_id,
+        context.is_warmup,
+    );
+    ensure_output_dir(&run_dir)?;
+
+    write_jsonl(&run_dir.join("janus_results.jsonl"), context.janus_rows)?;
+    write_jsonl(&run_dir.join("oxigraph_results.jsonl"), context.oxigraph_rows)?;
+
+    let mut canonical_janus = context.janus_rows.to_vec();
+    canonical_janus.sort_by(canonical_row_cmp);
+    write_jsonl(&run_dir.join("canonical_janus_results.jsonl"), &canonical_janus)?;
+
+    let mut canonical_oxigraph = context.oxigraph_rows.to_vec();
+    canonical_oxigraph.sort_by(canonical_row_cmp);
+    write_jsonl(&run_dir.join("canonical_oxigraph_results.jsonl"), &canonical_oxigraph)?;
+
+    let report = EquivalenceReport {
+        dataset_size_quads: context.dataset.dataset_size_quads,
+        event_count: context.dataset.event_count,
+        query_case: context.query_case.as_str().to_string(),
+        range_start_ms: context.range.start_ms,
+        range_end_ms: context.range.end_ms_exclusive,
+        range_width_ms: context.range.end_ms_exclusive.saturating_sub(context.range.start_ms),
+        janus_result_count: context.janus_rows.len(),
+        oxigraph_result_count: context.oxigraph_rows.len(),
+        janus_result_hash: context.janus_hash.to_string(),
+        oxigraph_result_hash: context.oxigraph_hash.to_string(),
+        equivalent: false,
+    };
+    fs::write(run_dir.join("equivalence_report.json"), serde_json::to_vec_pretty(&report)?)?;
+    Ok(())
+}
+
+fn debug_run_dir(
+    output_dir: &Path,
+    dataset_size_quads: usize,
+    query_case: HistoricalRangeQueryCase,
+    run_id: usize,
+    is_warmup: bool,
+) -> PathBuf {
+    output_dir
+        .join("equivalence_debug")
+        .join(dataset_size_quads.to_string())
+        .join(query_case.as_str())
+        .join(format!("run_{run_id:03}_{}", if is_warmup { "warmup" } else { "measured" }))
+}
+
+fn percentile(values: &[f64], pct: f64) -> f64 {
+    if values.is_empty() {
+        return 0.0;
+    }
+    let mut sorted = values.to_vec();
+    sorted.sort_by(|left, right| left.partial_cmp(right).unwrap_or(Ordering::Equal));
+    let rank = ((pct / 100.0) * (sorted.len().saturating_sub(1) as f64)).round() as usize;
+    sorted[rank]
+}
+
+fn mean(values: &[f64]) -> f64 {
+    if values.is_empty() {
+        0.0
+    } else {
+        values.iter().sum::<f64>() / values.len() as f64
+    }
+}
+
+fn dataset_label(dataset_size_quads: usize) -> String {
+    match dataset_size_quads {
+        10_000 => "10k".to_string(),
+        50_000 => "50k".to_string(),
+        100_000 => "100k".to_string(),
+        500_000 => "500k".to_string(),
+        value if value % 1_000_000 == 0 => format!("{}M", value / 1_000_000),
+        value if value % 1_000 == 0 => format!("{}k", value / 1_000),
+        value => value.to_string(),
+    }
+}
+
+fn unique_config(prefix: &str) -> StreamingConfig {
+    let counter = CONFIG_COUNTER.fetch_add(1, AtomicOrdering::Relaxed);
+    StreamingConfig {
+        segment_base_path: format!("/tmp/janus_{prefix}_{}_{}", now_ms(), counter),
+        max_batch_events: 1_000_000,
+        max_batch_age_seconds: 3_600,
+        max_batch_bytes: 1_000_000_000,
+        sparse_interval: 64,
+        entries_per_index_block: 256,
+    }
+}
+
+fn now_ms() -> u64 {
+    std::time::SystemTime::now()
+        .duration_since(std::time::UNIX_EPOCH)
+        .unwrap_or_default()
+        .as_millis() as u64
+}
+
+fn ensure_output_dir(path: &Path) -> Result<(), BoxError> {
+    fs::create_dir_all(path)?;
+    Ok(())
+}
+
+fn write_jsonl<T: Serialize>(path: &Path, rows: &[T]) -> Result<(), BoxError> {
+    let mut file = File::create(path)?;
+    for row in rows {
+        serde_json::to_writer(&mut file, row)?;
+        writeln!(file)?;
+    }
+    Ok(())
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn fixed_60s_range_is_bounded_at_six_thousand_results() {
+        let dataset = prepare_dataset(10_000).expect("dataset should build");
+        let range = range_for_case(&dataset, HistoricalRangeQueryCase::Fixed60sRange, 60)
+            .expect("range should build");
+        let results =
+            historical_range(&dataset.janus_storage, range.start_ms, range.end_ms_exclusive)
+                .expect("janus range should succeed");
+        assert_eq!(results.len(), 6_000);
+        assert_eq!(range.end_ms_exclusive - range.start_ms, 60_000);
+    }
+
+    #[test]
+    fn canonical_hash_is_order_independent() {
+        let left = vec![
+            CanonicalResultRow {
+                subject: "http://example.org/event/00000001".to_string(),
+                predicate: TIMESTAMP_PREDICATE.to_string(),
+                object: typed_timestamp_literal(1),
+                graph: String::new(),
+                timestamp_ms: 1,
+            },
+            CanonicalResultRow {
+                subject: "http://example.org/event/00000002".to_string(),
+                predicate: TIMESTAMP_PREDICATE.to_string(),
+                object: typed_timestamp_literal(2),
+                graph: String::new(),
+                timestamp_ms: 2,
+            },
+        ];
+        let mut right = left.clone();
+        right.reverse();
+        let mut sorted_left = left.clone();
+        sorted_left.sort_by(canonical_row_cmp);
+        right.sort_by(canonical_row_cmp);
+        assert_eq!(result_hash(&sorted_left).expect("hash"), result_hash(&right).expect("hash"));
+    }
+}
diff --git a/src/paper_bench/mod.rs b/src/paper_bench/mod.rs
new file mode 100644
index 0000000..c9f6e55
--- /dev/null
+++ b/src/paper_bench/mod.rs
@@ -0,0 +1,5 @@
+pub mod cli_output;
+pub mod external;
+pub mod harness;
+pub mod historical_range;
+pub mod query_defined_baseline;
diff --git a/src/paper_bench/query_defined_baseline.rs b/src/paper_bench/query_defined_baseline.rs
new file mode 100644
index 0000000..98ec82a
--- /dev/null
+++ b/src/paper_bench/query_defined_baseline.rs
@@ -0,0 +1,2420 @@
+use crate::{
+    core::RDFEvent,
+    execution::{HistoricalExecutor, ResultConverter},
+    paper_bench::harness::{collect_repro_metadata, ensure_output_dir},
+    parsing::janusql_parser::{
+        BaselineDefinition, BaselineGraphTemplate, GraphTermTemplate, JanusQLParser,
+        ParsedJanusQuery, SourceKind, TripleTemplate, WindowDefinition, WindowType,
+    },
+    querying::oxigraph_adapter::OxigraphAdapter,
+    storage::{segmented_storage::StreamingSegmentedStorage, util::StreamingConfig},
+    stream::live_stream_processing::LiveStreamProcessing,
+};
+use clap::ValueEnum;
+use oxigraph::model::{BlankNode, GraphName, NamedNode, NamedOrBlankNode, Quad, Term};
+use serde::Serialize;
+use std::sync::{
+    atomic::{AtomicBool, Ordering},
+    Mutex,
+};
+use std::{
+    collections::HashMap,
+    fs::File,
+    io::Write,
+    path::{Path, PathBuf},
+    sync::Arc,
+    thread,
+    time::{Duration, Instant, SystemTime, UNIX_EPOCH},
+};
+use sysinfo::{Pid, ProcessRefreshKind, ProcessesToUpdate, System};
+
+const PREFIX: &str = "http://example.org/";
+const STREAM_URI: &str = "http://example.org/stream";
+const BASELINE_GRAPH: &str = "http://example.org/dayBaseline";
+const BASELINE_QUERY_NAME: &str = "http://example.org/dayBaseline";
+const RESOURCE_SAMPLE_INTERVAL: Duration = Duration::from_millis(250);
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Serialize, ValueEnum)]
+#[serde(rename_all = "snake_case")]
+pub enum QueryDefinedBaselineProfile {
+    Smoke,
+}
+
+impl QueryDefinedBaselineProfile {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Smoke => "smoke",
+        }
+    }
+}
+
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Serialize, ValueEnum)]
+#[serde(rename_all = "snake_case")]
+pub enum LiveReplayMode {
+    Accelerated,
+    Realtime,
+}
+
+impl LiveReplayMode {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Accelerated => "accelerated",
+            Self::Realtime => "realtime",
+        }
+    }
+}
+
+#[derive(Clone, Debug)]
+pub struct QueryDefinedBaselineBenchmarkConfig {
+    pub profile: QueryDefinedBaselineProfile,
+    pub runs: usize,
+    pub warmup_runs: usize,
+    pub historical_events: Vec<usize>,
+    pub baseline_entities: Vec<usize>,
+    pub live_replay_mode: LiveReplayMode,
+    pub live_rate_hz: f64,
+    pub live_duration_seconds: Option<u64>,
+    pub live_window_size_seconds: Option<u64>,
+    pub live_window_slide_seconds: Option<u64>,
+    pub output_dir: Option<PathBuf>,
+    pub debug_lowered_query: bool,
+    pub verbose: bool,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineObservedRow {
+    pub sensor: String,
+    pub minute_avg_value: f64,
+    pub day_avg_value: Option<f64>,
+    pub difference: Option<f64>,
+    pub received_after_first_event_ms: f64,
+    pub timestamp_from: i64,
+    pub timestamp_to: i64,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineCorrectnessDiagnostics {
+    pub variant: String,
+    pub expected_result_count: usize,
+    pub observed_result_count: usize,
+    pub expected_emitted_windows: Option<usize>,
+    pub observed_emitted_windows: usize,
+    pub expected_variables: Vec<String>,
+    pub observed_variables: Vec<String>,
+    pub first_observed_rows: Vec<QueryDefinedBaselineObservedRow>,
+    pub reason: String,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineVariantMetrics {
+    pub variant: String,
+    pub run_index: usize,
+    pub historical_events: usize,
+    pub baseline_entities: usize,
+    pub live_replay_mode: String,
+    pub live_rate_hz: f64,
+    pub live_duration_seconds: Option<u64>,
+    pub live_window_size_seconds: Option<u64>,
+    pub live_window_slide_seconds: Option<u64>,
+    pub live_event_count: usize,
+    pub expected_emitted_windows: usize,
+    pub expected_full_windows: usize,
+    pub warmup_window_count: Option<usize>,
+    pub observed_emitted_windows: usize,
+    pub window_semantics_note: Option<String>,
+    pub historical_generation_ms: Option<f64>,
+    pub storage_write_ms: Option<f64>,
+    pub baseline_eval_ms: Option<f64>,
+    pub materialization_ms: Option<f64>,
+    pub static_injection_ms: Option<f64>,
+    pub historical_query_ms: Option<f64>,
+    pub baseline_materialization_ms: Option<f64>,
+    pub static_graph_injection_ms: Option<f64>,
+    pub live_startup_ms: f64,
+    pub first_result_latency_ms: f64,
+    pub peak_rss_mb: Option<f64>,
+    pub mean_rss_mb: Option<f64>,
+    pub peak_cpu_percent: Option<f64>,
+    pub mean_cpu_percent: Option<f64>,
+    pub sample_count: usize,
+    pub result_count: usize,
+    pub correctness_ok: bool,
+    pub correctness_diagnostics: Option<QueryDefinedBaselineCorrectnessDiagnostics>,
+    pub materialized_quad_count: Option<usize>,
+    pub baseline_binding_count: Option<usize>,
+    pub window_result_latencies_ms: Vec<f64>,
+    pub completed_window_latencies_ms: Vec<f64>,
+    pub completed_window_result_counts: Vec<usize>,
+    pub observed_rows: Vec<QueryDefinedBaselineObservedRow>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineComparisonRow {
+    pub historical_events: usize,
+    pub baseline_entities: usize,
+    pub is_warmup: bool,
+    pub run_index: usize,
+    pub observed_baseline_rows: usize,
+    pub observed_live_only_rows: usize,
+    pub baseline: QueryDefinedBaselineVariantMetrics,
+    pub live_only: QueryDefinedBaselineVariantMetrics,
+    pub live_startup_overhead_ms: f64,
+    pub first_result_overhead_ms: f64,
+    pub peak_rss_mb: Option<f64>,
+    pub mean_rss_mb: Option<f64>,
+    pub peak_cpu_percent: Option<f64>,
+    pub mean_cpu_percent: Option<f64>,
+    pub sample_count: usize,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineBenchmarkReport {
+    pub metadata: crate::paper_bench::harness::ReproMetadata,
+    pub profile: String,
+    pub live_replay_mode: String,
+    pub live_rate_hz: f64,
+    pub live_duration_seconds: Option<u64>,
+    pub live_window_size_seconds: Option<u64>,
+    pub live_window_slide_seconds: Option<u64>,
+    pub runs: usize,
+    pub warmup_runs: usize,
+    pub historical_events: Vec<usize>,
+    pub baseline_entities: Vec<usize>,
+    pub correctness_passed: bool,
+    pub output_dir: PathBuf,
+    pub comparisons: Vec<QueryDefinedBaselineComparisonRow>,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineMatrixSummaryRow {
+    pub profile: String,
+    pub historical_events: usize,
+    pub baseline_entities: usize,
+    pub runs: usize,
+    pub warmup_runs: usize,
+    pub correctness_rate: f64,
+    pub expected_emitted_windows: Option<f64>,
+    pub expected_full_windows: Option<f64>,
+    pub warmup_window_count: Option<f64>,
+    pub observed_emitted_windows_mean: f64,
+    pub observed_emitted_windows_std: f64,
+    pub observed_baseline_rows_mean: f64,
+    pub observed_baseline_rows_std: f64,
+    pub observed_live_only_rows_mean: f64,
+    pub observed_live_only_rows_std: f64,
+    pub historical_generation_ms_mean: Option<f64>,
+    pub historical_generation_ms_std: Option<f64>,
+    pub storage_write_ms_mean: Option<f64>,
+    pub storage_write_ms_std: Option<f64>,
+    pub peak_rss_mb_mean: Option<f64>,
+    pub peak_rss_mb_std: Option<f64>,
+    pub mean_rss_mb_mean: Option<f64>,
+    pub mean_rss_mb_std: Option<f64>,
+    pub peak_cpu_percent_mean: Option<f64>,
+    pub peak_cpu_percent_std: Option<f64>,
+    pub mean_cpu_percent_mean: Option<f64>,
+    pub mean_cpu_percent_std: Option<f64>,
+    pub baseline_eval_ms_mean: Option<f64>,
+    pub baseline_eval_ms_std: Option<f64>,
+    pub materialization_ms_mean: Option<f64>,
+    pub materialization_ms_std: Option<f64>,
+    pub static_injection_ms_mean: Option<f64>,
+    pub static_injection_ms_std: Option<f64>,
+    pub baseline_first_result_ms_mean: f64,
+    pub baseline_first_result_ms_std: f64,
+    pub live_only_first_result_ms_mean: f64,
+    pub live_only_first_result_ms_std: f64,
+    pub startup_overhead_ms_mean: f64,
+    pub startup_overhead_ms_std: f64,
+    pub first_result_overhead_ms_mean: f64,
+    pub first_result_overhead_ms_std: f64,
+    pub baseline_binding_count_mean: Option<f64>,
+    pub baseline_binding_count_std: Option<f64>,
+    pub materialized_quad_count_mean: Option<f64>,
+    pub materialized_quad_count_std: Option<f64>,
+    pub baseline_result_count_mean: f64,
+    pub baseline_result_count_std: f64,
+    pub live_only_result_count_mean: f64,
+    pub live_only_result_count_std: f64,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct QueryDefinedBaselineBenchmarkCsvRows {
+    pub matrix_summaries: Vec<QueryDefinedBaselineMatrixSummaryRow>,
+}
+
+struct PreparedStorage {
+    storage: Arc<StreamingSegmentedStorage>,
+    historical_min_timestamp: u64,
+    historical_max_timestamp: u64,
+    historical_generation_ms: f64,
+    storage_write_ms: f64,
+    live_events: Vec<RDFEvent>,
+}
+
+#[derive(Clone, Copy, Debug)]
+struct ResolvedLiveReplayConfig {
+    mode: LiveReplayMode,
+    rate_hz: f64,
+    live_duration_seconds: Option<u64>,
+    live_window_size_seconds: Option<u64>,
+    live_window_slide_seconds: Option<u64>,
+    live_event_count: usize,
+    event_interval_ms: f64,
+    expected_emitted_windows: usize,
+    expected_full_windows: usize,
+    warmup_window_count: Option<usize>,
+}
+
+struct HistoricalWriteStats {
+    min_timestamp: u64,
+    max_timestamp: u64,
+    generation_ms: f64,
+    storage_write_ms: f64,
+}
+
+#[derive(Clone, Debug)]
+struct ResourceSample {
+    rss_mb: f64,
+    cpu_percent: f64,
+}
+
+#[derive(Clone, Debug, Default)]
+struct ResourceSummary {
+    peak_rss_mb: Option<f64>,
+    mean_rss_mb: Option<f64>,
+    peak_cpu_percent: Option<f64>,
+    mean_cpu_percent: Option<f64>,
+    sample_count: usize,
+}
+
+struct ResourceSampler {
+    stop: Arc<AtomicBool>,
+    samples: Arc<Mutex<Vec<ResourceSample>>>,
+    handle: Option<thread::JoinHandle<()>>,
+}
+
+#[derive(Debug)]
+struct VariantRunData {
+    metrics: QueryDefinedBaselineVariantMetrics,
+}
+
+#[derive(Debug)]
+struct TimedBinding {
+    result: rsp_rs::BindingWithTimestamp,
+    received_after_first_event_ms: f64,
+}
+
+#[derive(Debug)]
+struct ObservedWindowSummary {
+    result_count: usize,
+    first_result_latency_ms: f64,
+}
+
+pub struct QueryDefinedBaselineBenchmarkOutcome {
+    pub report_path: PathBuf,
+    pub summary_csv_path: PathBuf,
+    pub summary_md_path: PathBuf,
+    pub report: QueryDefinedBaselineBenchmarkReport,
+    pub csv_rows: QueryDefinedBaselineBenchmarkCsvRows,
+}
+
+impl ResourceSampler {
+    fn start(interval: Duration) -> Self {
+        let stop = Arc::new(AtomicBool::new(false));
+        let samples = Arc::new(Mutex::new(Vec::new()));
+        let thread_stop = Arc::clone(&stop);
+        let thread_samples = Arc::clone(&samples);
+        let handle = thread::spawn(move || {
+            let pid: Pid = (std::process::id() as usize).into();
+            let mut system = System::new_all();
+            let refresh = |system: &mut System| {
+                system.refresh_processes_specifics(
+                    ProcessesToUpdate::Some(&[pid]),
+                    ProcessRefreshKind::new().with_memory().with_cpu(),
+                );
+            };
+
+            refresh(&mut system);
+            let mut next_tick = Instant::now();
+
+            loop {
+                if thread_stop.load(Ordering::Relaxed) {
+                    break;
+                }
+
+                next_tick += interval;
+                if let Some(remaining) = next_tick.checked_duration_since(Instant::now()) {
+                    thread::sleep(remaining);
+                }
+
+                if thread_stop.load(Ordering::Relaxed) {
+                    break;
+                }
+
+                refresh(&mut system);
+                if let Some(process) = system.process(pid) {
+                    let mut guard = thread_samples.lock().expect("resource samples mutex poisoned");
+                    guard.push(ResourceSample {
+                        rss_mb: process.memory() as f64 / (1024.0 * 1024.0),
+                        cpu_percent: process.cpu_usage() as f64,
+                    });
+                }
+            }
+        });
+
+        Self { stop, samples, handle: Some(handle) }
+    }
+
+    fn finish(mut self) -> ResourceSummary {
+        self.stop.store(true, Ordering::Relaxed);
+        if let Some(handle) = self.handle.take() {
+            let _ = handle.join();
+        }
+
+        let samples = self.samples.lock().expect("resource samples mutex poisoned");
+        summarize_resource_samples(samples.as_slice())
+    }
+}
+
+pub fn run_query_defined_baseline_benchmark(
+    config: QueryDefinedBaselineBenchmarkConfig,
+) -> Result<QueryDefinedBaselineBenchmarkOutcome, Box<dyn std::error::Error>> {
+    let output_dir = config.output_dir.clone().unwrap_or_else(default_output_dir);
+    ensure_output_dir(&output_dir)?;
+    let metadata = collect_repro_metadata();
+    let parser = JanusQLParser::new()?;
+    let live_replay = resolve_live_replay_config(&config)?;
+    let mut comparisons = Vec::new();
+
+    for &historical_events in &config.historical_events {
+        for &baseline_entities in &config.baseline_entities {
+            let prepared = prepare_storage(
+                config.profile,
+                historical_events,
+                baseline_entities,
+                config.verbose,
+            )?;
+
+            for run_index in 0..config.warmup_runs {
+                let comparison = run_single_comparison(
+                    &parser,
+                    &prepared,
+                    &live_replay,
+                    config.profile,
+                    historical_events,
+                    baseline_entities,
+                    run_index,
+                    true,
+                    config.debug_lowered_query,
+                    config.verbose,
+                )?;
+                comparisons.push(comparison);
+            }
+
+            for run_index in 0..config.runs {
+                let comparison = run_single_comparison(
+                    &parser,
+                    &prepared,
+                    &live_replay,
+                    config.profile,
+                    historical_events,
+                    baseline_entities,
+                    run_index,
+                    false,
+                    config.debug_lowered_query,
+                    config.verbose,
+                )?;
+                comparisons.push(comparison);
+            }
+        }
+    }
+
+    let report = QueryDefinedBaselineBenchmarkReport {
+        metadata,
+        profile: config.profile.as_str().to_string(),
+        live_replay_mode: live_replay.mode.as_str().to_string(),
+        live_rate_hz: live_replay.rate_hz,
+        live_duration_seconds: live_replay.live_duration_seconds,
+        live_window_size_seconds: live_replay.live_window_size_seconds,
+        live_window_slide_seconds: live_replay.live_window_slide_seconds,
+        runs: config.runs,
+        warmup_runs: config.warmup_runs,
+        historical_events: config.historical_events.clone(),
+        baseline_entities: config.baseline_entities.clone(),
+        correctness_passed: comparisons.iter().all(|comparison| {
+            comparison.baseline.correctness_ok && comparison.live_only.correctness_ok
+        }),
+        output_dir: output_dir.clone(),
+        comparisons: comparisons.clone(),
+    };
+
+    let report_path = output_dir.join("query_defined_baseline.raw.json");
+    let summary_csv_path = output_dir.join("query_defined_baseline.summary.csv");
+    let summary_md_path = output_dir.join("query_defined_baseline_results.md");
+
+    write_report_json(&report_path, &report)?;
+    let csv_rows = summarize_comparisons(&report);
+    write_summary_csv(&summary_csv_path, &csv_rows)?;
+    write_summary_markdown(&summary_md_path, &csv_rows)?;
+
+    Ok(QueryDefinedBaselineBenchmarkOutcome {
+        report_path,
+        summary_csv_path,
+        summary_md_path,
+        report,
+        csv_rows,
+    })
+}
+
+fn resolve_live_replay_config(
+    config: &QueryDefinedBaselineBenchmarkConfig,
+) -> Result<ResolvedLiveReplayConfig, Box<dyn std::error::Error>> {
+    if !config.live_rate_hz.is_finite() || config.live_rate_hz <= 0.0 {
+        return Err("--live-rate-hz must be greater than 0".into());
+    }
+
+    let resolved = match config.live_replay_mode {
+        LiveReplayMode::Accelerated => ResolvedLiveReplayConfig {
+            mode: LiveReplayMode::Accelerated,
+            rate_hz: config.live_rate_hz,
+            live_duration_seconds: None,
+            live_window_size_seconds: None,
+            live_window_slide_seconds: None,
+            live_event_count: 0,
+            event_interval_ms: 0.0,
+            expected_emitted_windows: 0,
+            expected_full_windows: 0,
+            warmup_window_count: None,
+        },
+        LiveReplayMode::Realtime => {
+            let live_duration_seconds = config.live_duration_seconds.unwrap_or(240);
+            let live_window_size_seconds = config.live_window_size_seconds.unwrap_or(120);
+            let live_window_slide_seconds = config.live_window_slide_seconds.unwrap_or(60);
+
+            if live_window_size_seconds == 0 {
+                return Err("--live-window-size-seconds must be greater than 0".into());
+            }
+            if live_window_slide_seconds == 0 {
+                return Err("--live-window-slide-seconds must be greater than 0".into());
+            }
+
+            let live_event_count =
+                ((live_duration_seconds as f64) * config.live_rate_hz).round() as usize;
+            let event_interval_ms = 1000.0 / config.live_rate_hz;
+            let expected_emitted_windows =
+                expected_emitted_windows(live_duration_seconds, live_window_slide_seconds);
+            let expected_full_windows = expected_full_windows(
+                live_duration_seconds,
+                live_window_size_seconds,
+                live_window_slide_seconds,
+            );
+
+            ResolvedLiveReplayConfig {
+                mode: LiveReplayMode::Realtime,
+                rate_hz: config.live_rate_hz,
+                live_duration_seconds: Some(live_duration_seconds),
+                live_window_size_seconds: Some(live_window_size_seconds),
+                live_window_slide_seconds: Some(live_window_slide_seconds),
+                live_event_count,
+                event_interval_ms,
+                expected_emitted_windows,
+                expected_full_windows,
+                warmup_window_count: Some(
+                    expected_emitted_windows.saturating_sub(expected_full_windows),
+                ),
+            }
+        }
+    };
+
+    Ok(resolved)
+}
+
+fn expected_emitted_windows(live_duration_seconds: u64, window_slide_seconds: u64) -> usize {
+    if window_slide_seconds == 0 {
+        return 0;
+    }
+
+    (live_duration_seconds / window_slide_seconds) as usize
+}
+
+fn expected_full_windows(
+    live_duration_seconds: u64,
+    window_size_seconds: u64,
+    window_slide_seconds: u64,
+) -> usize {
+    if live_duration_seconds < window_size_seconds {
+        return 0;
+    }
+
+    1 + ((live_duration_seconds - window_size_seconds) / window_slide_seconds) as usize
+}
+
+fn default_output_dir() -> PathBuf {
+    let ts = SystemTime::now().duration_since(UNIX_EPOCH).unwrap_or_default().as_millis();
+    PathBuf::from(format!("logs/benchmark/query_defined_baseline/{ts}"))
+}
+
+fn prepare_storage(
+    profile: QueryDefinedBaselineProfile,
+    historical_events_count: usize,
+    baseline_entities_count: usize,
+    verbose: bool,
+) -> Result<PreparedStorage, Box<dyn std::error::Error>> {
+    if historical_events_count == 0 {
+        return Err("historical_events must be at least 1".into());
+    }
+    if baseline_entities_count == 0 {
+        return Err("baseline_entities must be at least 1".into());
+    }
+    if historical_events_count < baseline_entities_count {
+        return Err("historical_events must be greater than or equal to baseline_entities".into());
+    }
+
+    let storage = StreamingSegmentedStorage::new(StreamingConfig {
+        segment_base_path: format!(
+            "/tmp/janus_query_defined_baseline_{}_{}_{}",
+            profile.as_str(),
+            historical_events_count,
+            baseline_entities_count
+        ),
+        max_batch_events: 1_000_000,
+        max_batch_age_seconds: 3600,
+        max_batch_bytes: 1_000_000_000,
+        sparse_interval: 64,
+        entries_per_index_block: 256,
+    })?;
+
+    let historical_stats = write_historical_events(
+        &storage,
+        historical_events_count,
+        baseline_entities_count,
+        verbose,
+    )?;
+    let historical_generation_ms = historical_stats.generation_ms;
+    let storage_write_ms = historical_stats.storage_write_ms;
+
+    let live_events = generate_accelerated_live_events(baseline_entities_count);
+
+    Ok(PreparedStorage {
+        storage: Arc::new(storage),
+        historical_min_timestamp: historical_stats.min_timestamp,
+        historical_max_timestamp: historical_stats.max_timestamp,
+        historical_generation_ms,
+        storage_write_ms,
+        live_events,
+    })
+}
+
+fn write_historical_events(
+    storage: &StreamingSegmentedStorage,
+    historical_events_count: usize,
+    baseline_entities_count: usize,
+    verbose: bool,
+) -> Result<HistoricalWriteStats, Box<dyn std::error::Error>> {
+    let mut min_timestamp = 0u64;
+    let mut max_timestamp = 0u64;
+    let mut initialized = false;
+    let mut timestamp = 10u64;
+    let mut generation_ms = 0.0;
+    let mut write_ms = 0.0;
+
+    for event_idx in 0..historical_events_count {
+        if verbose && event_idx > 0 && event_idx % 1_000_000 == 0 {
+            eprintln!(
+                "[query_defined_baseline] historical_events_written={event_idx}/{historical_events_count}"
+            );
+        }
+
+        let event_started = Instant::now();
+        let sensor_idx = event_idx % baseline_entities_count;
+        let value = 10 + sensor_idx as i64;
+        let event = RDFEvent::new(
+            timestamp,
+            &sensor_iri(sensor_idx),
+            &format!("{PREFIX}hasValue"),
+            &value.to_string(),
+            &format!("{PREFIX}stream"),
+        );
+        generation_ms += event_started.elapsed().as_secs_f64() * 1_000.0;
+
+        let write_started = Instant::now();
+        storage.write_rdf_event(event)?;
+        write_ms += write_started.elapsed().as_secs_f64() * 1_000.0;
+
+        if !initialized {
+            min_timestamp = timestamp;
+            max_timestamp = timestamp;
+            initialized = true;
+        } else {
+            min_timestamp = min_timestamp.min(timestamp);
+            max_timestamp = max_timestamp.max(timestamp);
+        }
+        timestamp += 10;
+    }
+
+    if !initialized {
+        return Err("missing historical benchmark events".into());
+    }
+
+    Ok(HistoricalWriteStats {
+        min_timestamp,
+        max_timestamp,
+        generation_ms,
+        storage_write_ms: write_ms,
+    })
+}
+
+fn generate_accelerated_live_events(baseline_entities_count: usize) -> Vec<RDFEvent> {
+    let mut events = Vec::with_capacity(baseline_entities_count);
+    for sensor_idx in 0..baseline_entities_count {
+        let timestamp = 1000 + (sensor_idx as u64 * 10);
+        let value = 20 + sensor_idx as i64 * 10;
+        events.push(RDFEvent::new(
+            timestamp,
+            &sensor_iri(sensor_idx),
+            &format!("{PREFIX}hasValue"),
+            &value.to_string(),
+            &format!("{PREFIX}stream"),
+        ));
+    }
+    events
+}
+
+fn generate_realtime_live_events(
+    baseline_entities_count: usize,
+    live_event_count: usize,
+    event_interval_ms: f64,
+) -> Vec<RDFEvent> {
+    let mut events = Vec::with_capacity(live_event_count);
+    let start_timestamp = 1_900_000_000_000u64;
+    for event_idx in 0..live_event_count {
+        let sensor_idx = event_idx % baseline_entities_count;
+        let timestamp = start_timestamp + ((event_idx as f64) * event_interval_ms).round() as u64;
+        let value = 20 + sensor_idx as i64 * 10;
+        events.push(RDFEvent::new(
+            timestamp,
+            &sensor_iri(sensor_idx),
+            &format!("{PREFIX}hasValue"),
+            &value.to_string(),
+            &format!("{PREFIX}stream"),
+        ));
+    }
+    events
+}
+
+fn build_live_events_for_replay(
+    prepared: &PreparedStorage,
+    live_replay: &ResolvedLiveReplayConfig,
+    baseline_entities_count: usize,
+) -> Vec<RDFEvent> {
+    match live_replay.mode {
+        LiveReplayMode::Accelerated => prepared.live_events.clone(),
+        LiveReplayMode::Realtime => generate_realtime_live_events(
+            baseline_entities_count,
+            live_replay.live_event_count,
+            live_replay.event_interval_ms,
+        ),
+    }
+}
+
+fn realtime_close_timestamp(
+    live_events: &[RDFEvent],
+    live_replay: &ResolvedLiveReplayConfig,
+) -> Result<i64, Box<dyn std::error::Error>> {
+    let last_timestamp = live_events.last().ok_or("missing live benchmark events")?.timestamp;
+    let window_size_ms = live_replay
+        .live_window_size_seconds
+        .ok_or("missing realtime window size")?
+        .saturating_mul(1000);
+    let event_interval_ms = live_replay.event_interval_ms.ceil() as u64;
+    let close_timestamp = last_timestamp
+        .saturating_add(window_size_ms)
+        .saturating_add(event_interval_ms)
+        .saturating_add(1);
+    Ok(i64::try_from(close_timestamp)?)
+}
+
+fn query_defined_baseline_query(
+    live_replay: LiveReplayMode,
+    window_size_ms: u64,
+    window_slide_ms: u64,
+) -> String {
+    let window_clause = match live_replay {
+        LiveReplayMode::Accelerated => "FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60000 STEP 1000]".to_string(),
+        LiveReplayMode::Realtime => format!(
+            "FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE {window_size_ms} STEP {window_slide_ms}]"
+        ),
+    };
+    format!(
+        r#"
+PREFIX ex: <{prefix}>
+
+{window_clause}
+FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [START 0 END 86400000]
+
+DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {{
+  ?sensor ex:hasValue ?value .
+}}
+GROUP BY ?sensor
+
+REGISTER RStream ex:output AS
+USING BASELINE ex:dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {{
+  WINDOW ex:liveMinute {{
+    ?sensor ex:hasValue ?value .
+  }}
+  GRAPH ex:dayBaseline {{
+    ?sensor ex:dayAvgValue ?dayAvgValue .
+  }}
+}}
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
+"#,
+        prefix = PREFIX,
+        window_clause = window_clause
+    )
+}
+
+fn smoke_historical_window(
+    min_timestamp: u64,
+    max_timestamp: u64,
+) -> Result<WindowDefinition, Box<dyn std::error::Error>> {
+    Ok(WindowDefinition {
+        window_name: format!("{PREFIX}historyDay"),
+        source_kind: SourceKind::Log,
+        stream_name: format!("{PREFIX}stream"),
+        width: 0,
+        slide: 0,
+        offset: None,
+        start: Some(min_timestamp),
+        end: Some(max_timestamp),
+        window_type: WindowType::HistoricalFixed,
+    })
+}
+
+fn live_only_query(
+    live_replay: LiveReplayMode,
+    window_size_ms: u64,
+    window_slide_ms: u64,
+) -> String {
+    let window_clause = match live_replay {
+        LiveReplayMode::Accelerated => "FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60 STEP 5]".to_string(),
+        LiveReplayMode::Realtime => format!(
+            "FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE {window_size_ms} STEP {window_slide_ms}]"
+        ),
+    };
+    format!(
+        r#"
+PREFIX : <{prefix}>
+
+{window_clause}
+
+REGISTER RStream :output AS
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+WHERE {{
+  WINDOW :liveMinute {{
+    ?sensor :hasValue ?value .
+  }}
+}}
+GROUP BY ?sensor
+"#,
+        prefix = PREFIX,
+        window_clause = window_clause
+    )
+}
+
+fn run_single_comparison(
+    parser: &JanusQLParser,
+    prepared: &PreparedStorage,
+    live_replay: &ResolvedLiveReplayConfig,
+    profile: QueryDefinedBaselineProfile,
+    historical_events: usize,
+    baseline_entities: usize,
+    run_index: usize,
+    is_warmup: bool,
+    debug_lowered_query: bool,
+    verbose: bool,
+) -> Result<QueryDefinedBaselineComparisonRow, Box<dyn std::error::Error>> {
+    let _ = profile;
+    let sampler = ResourceSampler::start(RESOURCE_SAMPLE_INTERVAL);
+    let comparison_result =
+        (|| -> Result<QueryDefinedBaselineComparisonRow, Box<dyn std::error::Error>> {
+            let baseline = run_baseline_variant(
+                parser,
+                prepared,
+                live_replay,
+                historical_events,
+                baseline_entities,
+                run_index,
+                is_warmup,
+                debug_lowered_query,
+                verbose,
+            )?;
+            let live_only = run_live_only_variant(
+                prepared,
+                live_replay,
+                historical_events,
+                baseline_entities,
+                run_index,
+                is_warmup,
+                debug_lowered_query,
+                verbose,
+            )?;
+
+            Ok(QueryDefinedBaselineComparisonRow {
+                historical_events,
+                baseline_entities,
+                is_warmup,
+                run_index,
+                observed_baseline_rows: baseline.metrics.result_count,
+                observed_live_only_rows: live_only.metrics.result_count,
+                live_startup_overhead_ms: (baseline.metrics.live_startup_ms
+                    - live_only.metrics.live_startup_ms)
+                    .max(0.0),
+                first_result_overhead_ms: (baseline.metrics.first_result_latency_ms
+                    - live_only.metrics.first_result_latency_ms)
+                    .max(0.0),
+                baseline: baseline.metrics,
+                live_only: live_only.metrics,
+                peak_rss_mb: None,
+                mean_rss_mb: None,
+                peak_cpu_percent: None,
+                mean_cpu_percent: None,
+                sample_count: 0,
+            })
+        })();
+    let resource_usage = sampler.finish();
+    let mut comparison = comparison_result?;
+    comparison.peak_rss_mb = resource_usage.peak_rss_mb;
+    comparison.mean_rss_mb = resource_usage.mean_rss_mb;
+    comparison.peak_cpu_percent = resource_usage.peak_cpu_percent;
+    comparison.mean_cpu_percent = resource_usage.mean_cpu_percent;
+    comparison.sample_count = resource_usage.sample_count;
+    Ok(comparison)
+}
+
+fn run_baseline_variant(
+    parser: &JanusQLParser,
+    prepared: &PreparedStorage,
+    live_replay: &ResolvedLiveReplayConfig,
+    historical_events: usize,
+    baseline_entities: usize,
+    run_index: usize,
+    is_warmup: bool,
+    debug_lowered_query: bool,
+    verbose: bool,
+) -> Result<VariantRunData, Box<dyn std::error::Error>> {
+    let window_size_ms = live_replay.live_window_size_seconds.unwrap_or(60).saturating_mul(1000);
+    let window_slide_ms = live_replay.live_window_slide_seconds.unwrap_or(5).saturating_mul(1000);
+    let query = query_defined_baseline_query(live_replay.mode, window_size_ms, window_slide_ms);
+    log_stage(verbose, "baseline", "parse_query");
+    let parsed = parser.parse(&query)?;
+    log_stage(verbose, "baseline", "execute_historical_query");
+    let historical_executor =
+        HistoricalExecutor::new(Arc::clone(&prepared.storage), OxigraphAdapter::new());
+    let historical_window = smoke_historical_window(
+        prepared.historical_min_timestamp,
+        prepared.historical_max_timestamp,
+    )?;
+
+    let historical_started = Instant::now();
+    let bindings = historical_executor.execute_fixed_window(
+        &historical_window,
+        parsed
+            .generated_baseline_queries
+            .first()
+            .ok_or("missing generated baseline query")?
+            .sparql_query
+            .as_str(),
+    )?;
+    let historical_query_ms = historical_started.elapsed().as_secs_f64() * 1_000.0;
+
+    log_stage(verbose, "baseline", "materialize_quads");
+    let materialize_started = Instant::now();
+    let quads = materialize_query_defined_baseline_quads(&parsed, &bindings)?;
+    let baseline_materialization_ms = materialize_started.elapsed().as_secs_f64() * 1_000.0;
+
+    if debug_lowered_query {
+        log_lowered_live_query("query_defined_baseline", &parsed.rspql_query);
+    }
+    log_stage(verbose, "baseline", "create_live_processor");
+    let mut processor = LiveStreamProcessing::new(parsed.rspql_query.clone())?;
+    processor.register_stream(STREAM_URI)?;
+    log_stage(verbose, "baseline", "inject_static_quads");
+    let injection_started = Instant::now();
+    for quad in &quads {
+        processor.add_static_quad(quad.clone());
+    }
+    let static_graph_injection_ms = injection_started.elapsed().as_secs_f64() * 1_000.0;
+
+    log_stage(verbose, "baseline", "start_live_processing");
+    let startup_started = Instant::now();
+    processor.start_processing()?;
+    let live_startup_ms = startup_started.elapsed().as_secs_f64() * 1_000.0;
+
+    let live_events = build_live_events_for_replay(prepared, live_replay, baseline_entities);
+    let expected_live_averages = expected_live_averages(&live_events);
+    let expected_day_averages = expected_day_averages(&bindings);
+    let live_event_start = Instant::now();
+    let mut collected = Vec::new();
+    match live_replay.mode {
+        LiveReplayMode::Accelerated => {
+            log_stage(verbose, "baseline", "send_live_events");
+            let first_event = live_events.first().ok_or("missing live benchmark events")?.clone();
+            processor.add_event(STREAM_URI, first_event)?;
+            for event in live_events.iter().skip(1) {
+                processor.add_event(STREAM_URI, event.clone())?;
+            }
+            log_stage(verbose, "baseline", "close_stream");
+            processor.close_stream(STREAM_URI, 10_000)?;
+            std::thread::sleep(Duration::from_millis(25));
+            log_stage(verbose, "baseline", "collect_results");
+            collected = collect_live_results(&processor, live_event_start, baseline_entities)?;
+        }
+        LiveReplayMode::Realtime => {
+            log_stage(verbose, "baseline", "send_live_events");
+            for (event_index, event) in live_events.iter().enumerate() {
+                wait_for_live_event_schedule(live_event_start, event_index, live_replay.rate_hz);
+                processor.add_event(STREAM_URI, event.clone())?;
+                drain_available_live_results(&processor, live_event_start, &mut collected)?;
+            }
+            log_stage(verbose, "baseline", "close_stream");
+            let close_timestamp = realtime_close_timestamp(&live_events, live_replay)?;
+            processor.close_stream(STREAM_URI, close_timestamp)?;
+            log_stage(verbose, "baseline", "collect_results");
+            collect_realtime_live_results(&processor, live_event_start, &mut collected)?;
+        }
+    }
+    let observed_rows = parse_live_rows(&collected)?;
+    log_stage(verbose, "baseline", "done");
+    let mut window_semantics_note = if live_replay.mode == LiveReplayMode::Realtime {
+        Some(format!(
+            "Realtime replay reports emitted windows separately from full windows; the first emission is the initial warm-up window and full windows follow at the logical duration horizon."
+        ))
+    } else {
+        None
+    };
+    let window_summaries = summarize_observed_windows(&observed_rows);
+    let first_result_latency_ms = observed_rows
+        .first()
+        .map(|row| row.received_after_first_event_ms)
+        .unwrap_or(0.0);
+    let window_result_latencies_ms = observed_rows
+        .iter()
+        .map(|row| row.received_after_first_event_ms)
+        .collect::<Vec<_>>();
+    let completed_window_latencies_ms = window_summaries
+        .iter()
+        .map(|window| window.first_result_latency_ms)
+        .collect::<Vec<_>>();
+    let completed_window_result_counts =
+        window_summaries.iter().map(|window| window.result_count).collect::<Vec<_>>();
+    let observed_emitted_windows = window_summaries.len();
+    let live_event_count = live_events.len();
+    if live_replay.mode == LiveReplayMode::Realtime
+        && observed_emitted_windows != live_replay.expected_emitted_windows
+    {
+        let boundary_note = format!(
+            "Observed {} emitted windows vs expected {}; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+            observed_emitted_windows, live_replay.expected_emitted_windows
+        );
+        window_semantics_note = Some(match window_semantics_note {
+            Some(existing) => format!("{existing} {boundary_note}"),
+            None => boundary_note,
+        });
+    }
+    let correctness_result = validate_baseline_rows(
+        &observed_rows,
+        &expected_live_averages,
+        &expected_day_averages,
+        baseline_entities,
+        live_replay,
+        observed_emitted_windows,
+        observed_rows.len(),
+        live_event_count,
+    );
+    let correctness_ok = correctness_result.is_ok();
+    let correctness_diagnostics = correctness_result.err().map(|reason| {
+        build_correctness_diagnostics(
+            "baseline",
+            baseline_entities,
+            &observed_rows,
+            Some(live_replay.expected_emitted_windows),
+            observed_emitted_windows,
+            vec![
+                "sensor".to_string(),
+                "minuteAvgValue".to_string(),
+                "dayAvgValue".to_string(),
+                "difference".to_string(),
+            ],
+            reason,
+        )
+    });
+    if verbose {
+        if let Some(diagnostics) = &correctness_diagnostics {
+            eprintln!("[baseline] correctness failed: {}", diagnostics.reason);
+            eprintln!(
+                "[baseline] expected_result_count={} observed_result_count={} expected_emitted_windows={:?} observed_emitted_windows={} expected_variables={:?} observed_variables={:?}",
+                diagnostics.expected_result_count,
+                diagnostics.observed_result_count,
+                diagnostics.expected_emitted_windows,
+                diagnostics.observed_emitted_windows,
+                diagnostics.expected_variables,
+                diagnostics.observed_variables
+            );
+            eprintln!("[baseline] first_observed_rows={:?}", diagnostics.first_observed_rows);
+        }
+    }
+    let metrics = QueryDefinedBaselineVariantMetrics {
+        variant: "baseline".to_string(),
+        run_index,
+        historical_events,
+        baseline_entities,
+        live_replay_mode: live_replay.mode.as_str().to_string(),
+        live_rate_hz: live_replay.rate_hz,
+        live_duration_seconds: live_replay.live_duration_seconds,
+        live_window_size_seconds: live_replay.live_window_size_seconds,
+        live_window_slide_seconds: live_replay.live_window_slide_seconds,
+        live_event_count,
+        expected_emitted_windows: live_replay.expected_emitted_windows,
+        expected_full_windows: live_replay.expected_full_windows,
+        warmup_window_count: live_replay.warmup_window_count,
+        observed_emitted_windows,
+        window_semantics_note,
+        historical_generation_ms: Some(prepared.historical_generation_ms),
+        storage_write_ms: Some(prepared.storage_write_ms),
+        baseline_eval_ms: Some(historical_query_ms),
+        materialization_ms: Some(baseline_materialization_ms),
+        static_injection_ms: Some(static_graph_injection_ms),
+        historical_query_ms: Some(historical_query_ms),
+        baseline_materialization_ms: Some(baseline_materialization_ms),
+        static_graph_injection_ms: Some(static_graph_injection_ms),
+        live_startup_ms,
+        first_result_latency_ms,
+        peak_rss_mb: None,
+        mean_rss_mb: None,
+        peak_cpu_percent: None,
+        mean_cpu_percent: None,
+        sample_count: 0,
+        result_count: observed_rows.len(),
+        correctness_ok,
+        correctness_diagnostics,
+        materialized_quad_count: Some(quads.len()),
+        baseline_binding_count: Some(bindings.len()),
+        window_result_latencies_ms,
+        completed_window_latencies_ms,
+        completed_window_result_counts,
+        observed_rows,
+    };
+
+    let _ = is_warmup;
+    Ok(VariantRunData { metrics })
+}
+
+fn run_live_only_variant(
+    prepared: &PreparedStorage,
+    live_replay: &ResolvedLiveReplayConfig,
+    historical_events: usize,
+    baseline_entities: usize,
+    run_index: usize,
+    is_warmup: bool,
+    debug_lowered_query: bool,
+    verbose: bool,
+) -> Result<VariantRunData, Box<dyn std::error::Error>> {
+    let _ = (run_index, is_warmup);
+    let window_size_ms = live_replay.live_window_size_seconds.unwrap_or(60).saturating_mul(1000);
+    let window_slide_ms = live_replay.live_window_slide_seconds.unwrap_or(5).saturating_mul(1000);
+    let live_query = live_only_query(live_replay.mode, window_size_ms, window_slide_ms);
+    log_stage(verbose, "live_only", "parse_query");
+    if debug_lowered_query {
+        log_lowered_live_query("live_only", &live_query);
+    }
+    log_stage(verbose, "live_only", "create_live_processor");
+    let mut processor = LiveStreamProcessing::new(live_query)?;
+    processor.register_stream(STREAM_URI)?;
+    log_stage(verbose, "live_only", "start_live_processing");
+    let startup_started = Instant::now();
+    processor.start_processing()?;
+    let live_startup_ms = startup_started.elapsed().as_secs_f64() * 1_000.0;
+
+    let live_events = build_live_events_for_replay(prepared, live_replay, baseline_entities);
+    let expected_live_averages = expected_live_averages(&live_events);
+    let live_event_start = Instant::now();
+    let mut collected = Vec::new();
+    match live_replay.mode {
+        LiveReplayMode::Accelerated => {
+            log_stage(verbose, "live_only", "send_live_events");
+            let first_event = live_events.first().ok_or("missing live benchmark events")?.clone();
+            processor.add_event(STREAM_URI, first_event)?;
+            for event in live_events.iter().skip(1) {
+                processor.add_event(STREAM_URI, event.clone())?;
+            }
+            log_stage(verbose, "live_only", "close_stream");
+            processor.close_stream(STREAM_URI, 10_000)?;
+            std::thread::sleep(Duration::from_millis(25));
+            log_stage(verbose, "live_only", "collect_results");
+            collected = collect_live_results(&processor, live_event_start, baseline_entities)?;
+        }
+        LiveReplayMode::Realtime => {
+            log_stage(verbose, "live_only", "send_live_events");
+            for (event_index, event) in live_events.iter().enumerate() {
+                wait_for_live_event_schedule(live_event_start, event_index, live_replay.rate_hz);
+                processor.add_event(STREAM_URI, event.clone())?;
+                drain_available_live_results(&processor, live_event_start, &mut collected)?;
+            }
+            log_stage(verbose, "live_only", "close_stream");
+            let close_timestamp = realtime_close_timestamp(&live_events, live_replay)?;
+            processor.close_stream(STREAM_URI, close_timestamp)?;
+            log_stage(verbose, "live_only", "collect_results");
+            collect_realtime_live_results(&processor, live_event_start, &mut collected)?;
+        }
+    }
+    let observed_rows = parse_live_rows(&collected)?;
+    log_stage(verbose, "live_only", "done");
+    let mut window_semantics_note = if live_replay.mode == LiveReplayMode::Realtime {
+        Some(format!(
+            "Realtime replay reports emitted windows separately from full windows; the first emission is the initial warm-up window and full windows follow at the logical duration horizon."
+        ))
+    } else {
+        None
+    };
+    let window_summaries = summarize_observed_windows(&observed_rows);
+    let first_result_latency_ms = observed_rows
+        .first()
+        .map(|row| row.received_after_first_event_ms)
+        .unwrap_or(0.0);
+    let window_result_latencies_ms = observed_rows
+        .iter()
+        .map(|row| row.received_after_first_event_ms)
+        .collect::<Vec<_>>();
+    let completed_window_latencies_ms = window_summaries
+        .iter()
+        .map(|window| window.first_result_latency_ms)
+        .collect::<Vec<_>>();
+    let completed_window_result_counts =
+        window_summaries.iter().map(|window| window.result_count).collect::<Vec<_>>();
+    let observed_emitted_windows = window_summaries.len();
+    let live_event_count = live_events.len();
+    if live_replay.mode == LiveReplayMode::Realtime
+        && observed_emitted_windows != live_replay.expected_emitted_windows
+    {
+        let boundary_note = format!(
+            "Observed {} emitted windows vs expected {}; the difference is typically caused by inclusive/exclusive window boundary behavior on a window that lands exactly on the replay horizon.",
+            observed_emitted_windows, live_replay.expected_emitted_windows
+        );
+        window_semantics_note = Some(match window_semantics_note {
+            Some(existing) => format!("{existing} {boundary_note}"),
+            None => boundary_note,
+        });
+    }
+    let correctness_result = validate_live_only_rows(
+        &observed_rows,
+        &expected_live_averages,
+        baseline_entities,
+        live_replay,
+        observed_emitted_windows,
+        observed_rows.len(),
+        live_event_count,
+    );
+    let correctness_ok = correctness_result.is_ok();
+    let correctness_diagnostics = correctness_result.err().map(|reason| {
+        build_correctness_diagnostics(
+            "live_only",
+            baseline_entities,
+            &observed_rows,
+            if live_replay.mode == LiveReplayMode::Realtime {
+                Some(live_replay.expected_emitted_windows)
+            } else {
+                None
+            },
+            observed_emitted_windows,
+            vec!["sensor".to_string(), "minuteAvgValue".to_string()],
+            reason,
+        )
+    });
+    if verbose {
+        if let Some(diagnostics) = &correctness_diagnostics {
+            eprintln!("[live_only] correctness failed: {}", diagnostics.reason);
+            eprintln!(
+                "[live_only] expected_result_count={} observed_result_count={} expected_emitted_windows={:?} observed_emitted_windows={} expected_variables={:?} observed_variables={:?}",
+                diagnostics.expected_result_count,
+                diagnostics.observed_result_count,
+                diagnostics.expected_emitted_windows,
+                diagnostics.observed_emitted_windows,
+                diagnostics.expected_variables,
+                diagnostics.observed_variables
+            );
+            eprintln!("[live_only] first_observed_rows={:?}", diagnostics.first_observed_rows);
+        }
+    }
+    let metrics = QueryDefinedBaselineVariantMetrics {
+        variant: "live_only".to_string(),
+        run_index,
+        historical_events,
+        baseline_entities,
+        live_replay_mode: live_replay.mode.as_str().to_string(),
+        live_rate_hz: live_replay.rate_hz,
+        live_duration_seconds: live_replay.live_duration_seconds,
+        live_window_size_seconds: live_replay.live_window_size_seconds,
+        live_window_slide_seconds: live_replay.live_window_slide_seconds,
+        live_event_count,
+        expected_emitted_windows: live_replay.expected_emitted_windows,
+        expected_full_windows: live_replay.expected_full_windows,
+        warmup_window_count: live_replay.warmup_window_count,
+        observed_emitted_windows,
+        window_semantics_note,
+        historical_generation_ms: Some(prepared.historical_generation_ms),
+        storage_write_ms: Some(prepared.storage_write_ms),
+        baseline_eval_ms: None,
+        materialization_ms: None,
+        static_injection_ms: None,
+        historical_query_ms: None,
+        baseline_materialization_ms: None,
+        static_graph_injection_ms: None,
+        live_startup_ms,
+        first_result_latency_ms,
+        peak_rss_mb: None,
+        mean_rss_mb: None,
+        peak_cpu_percent: None,
+        mean_cpu_percent: None,
+        sample_count: 0,
+        result_count: observed_rows.len(),
+        correctness_ok,
+        correctness_diagnostics,
+        materialized_quad_count: None,
+        baseline_binding_count: None,
+        window_result_latencies_ms,
+        completed_window_latencies_ms,
+        completed_window_result_counts,
+        observed_rows,
+    };
+
+    Ok(VariantRunData { metrics })
+}
+
+fn sensor_iri(sensor_idx: usize) -> String {
+    format!("{PREFIX}sensor{sensor_idx}")
+}
+
+fn log_stage(verbose: bool, variant: &str, stage: &str) {
+    if verbose {
+        eprintln!("[{variant}] stage={stage}");
+    }
+}
+
+fn log_lowered_live_query(label: &str, query: &str) {
+    eprintln!("[{}] lowered live query:", label);
+    for (index, line) in query.lines().enumerate() {
+        eprintln!("{:>4} | {}", index + 1, line);
+    }
+}
+
+fn wait_for_live_event_schedule(replay_start: Instant, event_index: usize, rate_hz: f64) {
+    let target = replay_start + Duration::from_secs_f64(event_index as f64 / rate_hz);
+    if let Some(remaining) = target.checked_duration_since(Instant::now()) {
+        std::thread::sleep(remaining);
+    }
+}
+
+fn drain_available_live_results(
+    processor: &LiveStreamProcessing,
+    first_event_started: Instant,
+    results: &mut Vec<TimedBinding>,
+) -> Result<bool, Box<dyn std::error::Error>> {
+    let mut made_progress = false;
+    while let Some(result) = processor.try_receive_result()? {
+        let received_after_first_event_ms = first_event_started.elapsed().as_secs_f64() * 1_000.0;
+        results.push(TimedBinding { result, received_after_first_event_ms });
+        made_progress = true;
+    }
+
+    Ok(made_progress)
+}
+
+fn collect_realtime_live_results(
+    processor: &LiveStreamProcessing,
+    first_event_started: Instant,
+    results: &mut Vec<TimedBinding>,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let idle_timeout = Duration::from_millis(250);
+    let deadline = Instant::now() + Duration::from_secs(10);
+    let mut last_progress = Instant::now();
+
+    loop {
+        if drain_available_live_results(processor, first_event_started, results)? {
+            last_progress = Instant::now();
+        } else if last_progress.elapsed() >= idle_timeout {
+            break;
+        }
+
+        if Instant::now() >= deadline {
+            break;
+        }
+
+        std::thread::sleep(Duration::from_millis(5));
+    }
+
+    if results.is_empty() {
+        return Err("timed out waiting for realtime live results".into());
+    }
+
+    Ok(())
+}
+
+fn summarize_observed_windows(
+    rows: &[QueryDefinedBaselineObservedRow],
+) -> Vec<ObservedWindowSummary> {
+    let mut by_window: std::collections::BTreeMap<
+        (i64, i64),
+        Vec<&QueryDefinedBaselineObservedRow>,
+    > = std::collections::BTreeMap::new();
+
+    for row in rows {
+        by_window.entry((row.timestamp_from, row.timestamp_to)).or_default().push(row);
+    }
+
+    by_window
+        .into_iter()
+        .map(|((_timestamp_from, _timestamp_to), rows)| ObservedWindowSummary {
+            result_count: rows.len(),
+            first_result_latency_ms: rows
+                .iter()
+                .map(|row| row.received_after_first_event_ms)
+                .fold(f64::INFINITY, f64::min),
+        })
+        .collect()
+}
+
+fn parse_live_rows(
+    results: &[TimedBinding],
+) -> Result<Vec<QueryDefinedBaselineObservedRow>, Box<dyn std::error::Error>> {
+    let converter = ResultConverter::new("query_defined_baseline".to_string());
+    let mut rows = Vec::new();
+
+    for result in results {
+        let converted = converter.from_live_binding(result.result.clone());
+        let binding = converted.bindings.first().ok_or("live result did not contain bindings")?;
+
+        let sensor = binding.get("sensor").cloned().ok_or("live result missing sensor binding")?;
+        let minute_avg_value = parse_numeric(
+            binding
+                .get("minuteAvgValue")
+                .ok_or("live result missing minuteAvgValue binding")?,
+        )?;
+        let day_avg_value =
+            binding.get("dayAvgValue").map(|value| parse_numeric(value)).transpose()?;
+        let difference = binding.get("difference").map(|value| parse_numeric(value)).transpose()?;
+
+        let observed = QueryDefinedBaselineObservedRow {
+            sensor,
+            minute_avg_value,
+            day_avg_value,
+            difference,
+            received_after_first_event_ms: result.received_after_first_event_ms,
+            timestamp_from: result.result.timestamp_from,
+            timestamp_to: result.result.timestamp_to,
+        };
+        rows.push(observed);
+    }
+
+    rows.sort_by(|left, right| {
+        left.timestamp_from
+            .cmp(&right.timestamp_from)
+            .then_with(|| left.timestamp_to.cmp(&right.timestamp_to))
+            .then_with(|| left.sensor.cmp(&right.sensor))
+    });
+
+    Ok(rows)
+}
+
+fn collect_live_results(
+    processor: &LiveStreamProcessing,
+    first_event_started: Instant,
+    expected_results: usize,
+) -> Result<Vec<TimedBinding>, Box<dyn std::error::Error>> {
+    let deadline = Instant::now() + Duration::from_secs(600);
+    let mut timed_results = Vec::new();
+    let mut last_progress = Instant::now();
+
+    loop {
+        let mut made_progress = false;
+        while let Some(result) = processor.try_receive_result()? {
+            let received_after_first_event_ms =
+                first_event_started.elapsed().as_secs_f64() * 1_000.0;
+            timed_results.push(TimedBinding { result, received_after_first_event_ms });
+            if timed_results.len() >= expected_results {
+                return Ok(timed_results);
+            }
+            made_progress = true;
+            last_progress = Instant::now();
+        }
+
+        if made_progress && last_progress.elapsed() >= Duration::from_millis(50) {
+            break;
+        }
+
+        if Instant::now() > deadline {
+            break;
+        }
+
+        std::thread::sleep(Duration::from_millis(5));
+    }
+
+    if timed_results.is_empty() {
+        return Err("timed out waiting for live results".into());
+    }
+
+    Ok(timed_results)
+}
+
+fn expected_live_averages(live_events: &[RDFEvent]) -> HashMap<String, f64> {
+    let mut by_sensor: HashMap<String, (f64, usize)> = HashMap::new();
+    for event in live_events {
+        let sensor = normalize_binding_term(&event.subject.to_string());
+        let value = event.object.to_string().trim().parse::<f64>().unwrap_or(0.0);
+        let entry = by_sensor.entry(sensor).or_insert((0.0, 0));
+        entry.0 += value;
+        entry.1 += 1;
+    }
+
+    by_sensor
+        .into_iter()
+        .map(|(sensor, (sum, count))| (sensor, if count == 0 { 0.0 } else { sum / count as f64 }))
+        .collect()
+}
+
+fn expected_day_averages(bindings: &[HashMap<String, String>]) -> HashMap<String, f64> {
+    let mut expected = HashMap::new();
+    for binding in bindings {
+        if let (Some(sensor), Some(day_avg)) = (binding.get("sensor"), binding.get("dayAvgValue")) {
+            if let Ok(value) = parse_numeric(day_avg) {
+                expected.insert(normalize_binding_term(sensor), value);
+            }
+        }
+    }
+
+    expected
+}
+
+fn observed_query_variables(rows: &[QueryDefinedBaselineObservedRow]) -> Vec<String> {
+    let mut vars = vec!["sensor".to_string(), "minuteAvgValue".to_string()];
+    if rows.iter().any(|row| row.day_avg_value.is_some()) {
+        vars.push("dayAvgValue".to_string());
+    }
+    if rows.iter().any(|row| row.difference.is_some()) {
+        vars.push("difference".to_string());
+    }
+    vars
+}
+
+fn build_correctness_diagnostics(
+    variant: &str,
+    expected_result_count: usize,
+    observed_rows: &[QueryDefinedBaselineObservedRow],
+    expected_emitted_windows: Option<usize>,
+    observed_emitted_windows: usize,
+    expected_variables: Vec<String>,
+    reason: String,
+) -> QueryDefinedBaselineCorrectnessDiagnostics {
+    QueryDefinedBaselineCorrectnessDiagnostics {
+        variant: variant.to_string(),
+        expected_result_count,
+        observed_result_count: observed_rows.len(),
+        expected_emitted_windows,
+        observed_emitted_windows,
+        expected_variables,
+        observed_variables: observed_query_variables(observed_rows),
+        first_observed_rows: observed_rows.iter().take(3).cloned().collect(),
+        reason,
+    }
+}
+
+fn validate_baseline_rows(
+    rows: &[QueryDefinedBaselineObservedRow],
+    expected_live_averages: &HashMap<String, f64>,
+    expected_day_averages: &HashMap<String, f64>,
+    expected_entities: usize,
+    live_replay: &ResolvedLiveReplayConfig,
+    observed_emitted_windows: usize,
+    observed_row_count: usize,
+    live_event_count: usize,
+) -> Result<(), String> {
+    if expected_day_averages.len() != expected_entities {
+        return Err(format!(
+            "expected {} baseline bindings but found {}",
+            expected_entities,
+            expected_day_averages.len()
+        ));
+    }
+    if observed_row_count != expected_entities {
+        return Err(format!(
+            "expected {} baseline rows but observed {}",
+            expected_entities, observed_row_count
+        ));
+    }
+    if live_replay.mode == LiveReplayMode::Realtime {
+        if live_event_count != live_replay.live_event_count {
+            return Err(format!(
+                "expected {} live events but observed {}",
+                live_replay.live_event_count, live_event_count
+            ));
+        }
+        if observed_emitted_windows != live_replay.expected_emitted_windows {
+            return Err(format!(
+                "expected {} emitted windows but observed {}",
+                live_replay.expected_emitted_windows, observed_emitted_windows
+            ));
+        }
+        if summarize_observed_windows(rows).len() != live_replay.expected_emitted_windows {
+            return Err(format!(
+                "expected {} summarized windows but observed {}",
+                live_replay.expected_emitted_windows,
+                summarize_observed_windows(rows).len()
+            ));
+        }
+    }
+
+    for row in rows {
+        let expected_live = expected_live_averages
+            .get(&row.sensor)
+            .ok_or_else(|| format!("missing expected live aggregate for sensor {}", row.sensor))?;
+        if (row.minute_avg_value - expected_live).abs() > 0.000_001 {
+            return Err(format!(
+                "sensor {} minuteAvgValue {:.6} did not match expected {:.6}",
+                row.sensor, row.minute_avg_value, expected_live
+            ));
+        }
+        let expected_day = expected_day_averages
+            .get(&row.sensor)
+            .ok_or_else(|| format!("missing expected day aggregate for sensor {}", row.sensor))?;
+        let day_avg = row
+            .day_avg_value
+            .ok_or_else(|| format!("sensor {} is missing dayAvgValue", row.sensor))?;
+        if (day_avg - expected_day).abs() > 0.000_001 {
+            return Err(format!(
+                "sensor {} dayAvgValue {:.6} did not match expected {:.6}",
+                row.sensor, day_avg, expected_day
+            ));
+        }
+        let difference = row
+            .difference
+            .ok_or_else(|| format!("sensor {} is missing difference", row.sensor))?;
+        if (row.minute_avg_value - day_avg - difference).abs() > 0.000_001 {
+            return Err(format!(
+                "sensor {} difference {:.6} was not minuteAvgValue - dayAvgValue",
+                row.sensor, difference
+            ));
+        }
+    }
+
+    Ok(())
+}
+
+fn validate_live_only_rows(
+    rows: &[QueryDefinedBaselineObservedRow],
+    expected_live_averages: &HashMap<String, f64>,
+    expected_entities: usize,
+    live_replay: &ResolvedLiveReplayConfig,
+    observed_emitted_windows: usize,
+    observed_row_count: usize,
+    live_event_count: usize,
+) -> Result<(), String> {
+    if observed_row_count != expected_entities {
+        return Err(format!(
+            "expected {} live-only rows but observed {}",
+            expected_entities, observed_row_count
+        ));
+    }
+    if live_replay.mode == LiveReplayMode::Realtime {
+        if live_event_count != live_replay.live_event_count {
+            return Err(format!(
+                "expected {} live events but observed {}",
+                live_replay.live_event_count, live_event_count
+            ));
+        }
+        if observed_emitted_windows != live_replay.expected_emitted_windows {
+            return Err(format!(
+                "expected {} emitted windows but observed {}",
+                live_replay.expected_emitted_windows, observed_emitted_windows
+            ));
+        }
+        if summarize_observed_windows(rows).len() != live_replay.expected_emitted_windows {
+            return Err(format!(
+                "expected {} summarized windows but observed {}",
+                live_replay.expected_emitted_windows,
+                summarize_observed_windows(rows).len()
+            ));
+        }
+    }
+
+    for row in rows {
+        let expected_live = expected_live_averages
+            .get(&row.sensor)
+            .ok_or_else(|| format!("missing expected live aggregate for sensor {}", row.sensor))?;
+        if (row.minute_avg_value - expected_live).abs() > 0.000_001 {
+            return Err(format!(
+                "sensor {} minuteAvgValue {:.6} did not match expected {:.6}",
+                row.sensor, row.minute_avg_value, expected_live
+            ));
+        }
+        if row.day_avg_value.is_some() {
+            return Err(format!("sensor {} unexpectedly produced dayAvgValue", row.sensor));
+        }
+        if row.difference.is_some() {
+            return Err(format!("sensor {} unexpectedly produced difference", row.sensor));
+        }
+    }
+
+    Ok(())
+}
+
+fn parse_numeric(raw: &str) -> Result<f64, Box<dyn std::error::Error>> {
+    let trimmed = raw.trim();
+    let cleaned = trimmed
+        .strip_prefix('"')
+        .and_then(|value| value.split('"').next())
+        .unwrap_or(trimmed)
+        .split("^^")
+        .next()
+        .unwrap_or(trimmed);
+    Ok(cleaned.parse::<f64>()?)
+}
+
+fn materialize_query_defined_baseline_quads(
+    parsed: &ParsedJanusQuery,
+    bindings: &[HashMap<String, String>],
+) -> Result<Vec<Quad>, Box<dyn std::error::Error>> {
+    let definition = parsed
+        .ast
+        .baseline_definitions
+        .iter()
+        .find(|definition| definition.name == BASELINE_QUERY_NAME)
+        .ok_or("missing baseline definition")?;
+    let template = parsed
+        .baseline_graph_templates
+        .iter()
+        .find(|template| template.baseline_name == BASELINE_QUERY_NAME)
+        .ok_or("missing baseline graph template")?;
+
+    let graph_name = GraphName::NamedNode(NamedNode::new(BASELINE_GRAPH)?);
+    let mut quads = Vec::new();
+    for binding in bindings {
+        for triple in &template.triples {
+            let subject = resolve_subject_term(triple, binding)?;
+            let predicate = resolve_predicate_term(triple)?;
+            let object = resolve_object_term(triple, binding)?;
+            quads.push(Quad::new(subject, predicate, object, graph_name.clone()));
+        }
+    }
+
+    validate_template_against_definition(definition, template)?;
+    Ok(quads)
+}
+
+fn validate_template_against_definition(
+    definition: &BaselineDefinition,
+    template: &BaselineGraphTemplate,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let output_variables = definition
+        .output_variables
+        .iter()
+        .map(|variable| variable.trim_start_matches('?'))
+        .collect::<std::collections::HashSet<_>>();
+
+    for triple in &template.triples {
+        for term in [&triple.subject, &triple.object] {
+            if let GraphTermTemplate::Variable(variable_name) = term {
+                if !output_variables.contains(variable_name.as_str()) {
+                    return Err(format!(
+                        "template references variable '?{}' that is not produced by the baseline SELECT output",
+                        variable_name
+                    )
+                    .into());
+                }
+            }
+        }
+
+        if matches!(triple.predicate, GraphTermTemplate::Variable(_)) {
+            return Err("baseline GRAPH template predicates must be concrete IRIs".into());
+        }
+    }
+
+    Ok(())
+}
+
+fn resolve_subject_term(
+    triple: &TripleTemplate,
+    binding: &HashMap<String, String>,
+) -> Result<NamedOrBlankNode, Box<dyn std::error::Error>> {
+    match &triple.subject {
+        GraphTermTemplate::Variable(name) => parse_named_or_blank_node(
+            binding
+                .get(name)
+                .ok_or_else(|| format!("missing GRAPH template variable '?{}'", name))?,
+        ),
+        GraphTermTemplate::Iri(iri) => parse_named_or_blank_node(iri),
+        GraphTermTemplate::Literal(raw) => Err(format!(
+            "GRAPH template has a literal subject '{}', but subjects must be IRIs or blank nodes",
+            raw
+        )
+        .into()),
+    }
+}
+
+fn resolve_predicate_term(
+    triple: &TripleTemplate,
+) -> Result<NamedNode, Box<dyn std::error::Error>> {
+    match &triple.predicate {
+        GraphTermTemplate::Iri(iri) => Ok(NamedNode::new(iri.clone())?),
+        GraphTermTemplate::Variable(name) => {
+            Err(format!("GRAPH template uses variable predicate '?{}'", name).into())
+        }
+        GraphTermTemplate::Literal(raw) => Err(format!(
+            "GRAPH template has a literal predicate '{}', but predicates must be IRIs",
+            raw
+        )
+        .into()),
+    }
+}
+
+fn resolve_object_term(
+    triple: &TripleTemplate,
+    binding: &HashMap<String, String>,
+) -> Result<Term, Box<dyn std::error::Error>> {
+    match &triple.object {
+        GraphTermTemplate::Variable(name) => {
+            let raw_value = binding
+                .get(name)
+                .ok_or_else(|| format!("missing GRAPH template variable '?{}'", name))?;
+            Ok(parse_term(raw_value)?)
+        }
+        GraphTermTemplate::Iri(iri) => Ok(parse_term(iri)?),
+        GraphTermTemplate::Literal(raw) => Ok(Term::Literal(parse_literal_term(raw)?)),
+    }
+}
+
+fn parse_named_or_blank_node(raw: &str) -> Result<NamedOrBlankNode, Box<dyn std::error::Error>> {
+    let trimmed = raw.trim();
+    if let Some(name) = trimmed.strip_prefix("_:") {
+        Ok(NamedOrBlankNode::BlankNode(BlankNode::new(name)?))
+    } else {
+        let iri = trimmed.trim_start_matches('<').trim_end_matches('>');
+        Ok(NamedOrBlankNode::NamedNode(NamedNode::new(iri)?))
+    }
+}
+
+fn parse_term(raw: &str) -> Result<Term, Box<dyn std::error::Error>> {
+    let trimmed = raw.trim();
+    if trimmed.starts_with("_:")
+        || trimmed.starts_with('<')
+        || trimmed.starts_with("http://")
+        || trimmed.starts_with("https://")
+    {
+        if let Some(name) = trimmed.strip_prefix("_:") {
+            return Ok(Term::BlankNode(BlankNode::new(name)?));
+        }
+        let iri = trimmed.trim_start_matches('<').trim_end_matches('>');
+        return Ok(Term::NamedNode(NamedNode::new(iri)?));
+    }
+
+    Ok(Term::Literal(parse_literal_term(trimmed)?))
+}
+
+fn parse_literal_term(raw: &str) -> Result<oxigraph::model::Literal, Box<dyn std::error::Error>> {
+    let trimmed = raw.trim();
+    if let Ok(value) = trimmed.parse::<i64>() {
+        return Ok(oxigraph::model::Literal::new_typed_literal(
+            value.to_string(),
+            NamedNode::new("http://www.w3.org/2001/XMLSchema#integer")?,
+        ));
+    }
+    if let Ok(value) = trimmed.parse::<f64>() {
+        return Ok(oxigraph::model::Literal::new_typed_literal(
+            value.to_string(),
+            NamedNode::new("http://www.w3.org/2001/XMLSchema#decimal")?,
+        ));
+    }
+
+    if !trimmed.starts_with('"') {
+        return Ok(oxigraph::model::Literal::new_simple_literal(trimmed));
+    }
+
+    let (lexical, suffix) = split_literal_lexical_and_suffix(trimmed)?;
+    let lexical = unescape_literal_lexical(lexical);
+
+    if let Some(language) = suffix.strip_prefix('@') {
+        return Ok(oxigraph::model::Literal::new_language_tagged_literal(lexical, language)?);
+    }
+
+    if let Some(datatype_iri) = suffix.strip_prefix("^^") {
+        let datatype = if datatype_iri.starts_with('<') && datatype_iri.ends_with('>') {
+            &datatype_iri[1..datatype_iri.len() - 1]
+        } else {
+            datatype_iri
+        };
+        return Ok(oxigraph::model::Literal::new_typed_literal(lexical, NamedNode::new(datatype)?));
+    }
+
+    Ok(oxigraph::model::Literal::new_simple_literal(lexical))
+}
+
+fn split_literal_lexical_and_suffix(raw: &str) -> Result<(&str, &str), Box<dyn std::error::Error>> {
+    let mut escaped = false;
+
+    for (index, ch) in raw.char_indices().skip(1) {
+        if escaped {
+            escaped = false;
+            continue;
+        }
+
+        match ch {
+            '\\' => escaped = true,
+            '"' => return Ok((&raw[1..index], raw[index + 1..].trim())),
+            _ => {}
+        }
+    }
+
+    Err("missing closing quote in literal".into())
+}
+
+fn unescape_literal_lexical(lexical: &str) -> String {
+    let mut result = String::with_capacity(lexical.len());
+    let mut chars = lexical.chars();
+
+    while let Some(ch) = chars.next() {
+        if ch == '\\' {
+            if let Some(next) = chars.next() {
+                match next {
+                    '\\' => result.push('\\'),
+                    '"' => result.push('"'),
+                    'n' => result.push('\n'),
+                    'r' => result.push('\r'),
+                    't' => result.push('\t'),
+                    other => {
+                        result.push('\\');
+                        result.push(other);
+                    }
+                }
+            } else {
+                result.push('\\');
+            }
+        } else {
+            result.push(ch);
+        }
+    }
+
+    result
+}
+
+fn write_report_json(
+    path: &Path,
+    report: &QueryDefinedBaselineBenchmarkReport,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let file = File::create(path)?;
+    serde_json::to_writer_pretty(file, report)?;
+    Ok(())
+}
+
+fn summarize_comparisons(
+    report: &QueryDefinedBaselineBenchmarkReport,
+) -> QueryDefinedBaselineBenchmarkCsvRows {
+    let mut by_config: HashMap<(usize, usize), Vec<&QueryDefinedBaselineComparisonRow>> =
+        HashMap::new();
+    for comparison in &report.comparisons {
+        if comparison.is_warmup {
+            continue;
+        }
+        by_config
+            .entry((comparison.historical_events, comparison.baseline_entities))
+            .or_default()
+            .push(comparison);
+    }
+
+    let mut matrix_summaries = by_config
+        .into_iter()
+        .map(|((historical_events, baseline_entities), rows)| {
+            summarize_matrix_config(
+                &report.profile,
+                historical_events,
+                baseline_entities,
+                report.warmup_runs,
+                rows,
+            )
+        })
+        .collect::<Vec<_>>();
+
+    matrix_summaries.sort_by(|left, right| {
+        left.historical_events
+            .cmp(&right.historical_events)
+            .then_with(|| left.baseline_entities.cmp(&right.baseline_entities))
+    });
+
+    QueryDefinedBaselineBenchmarkCsvRows { matrix_summaries }
+}
+
+fn summarize_matrix_config(
+    profile: &str,
+    historical_events: usize,
+    baseline_entities: usize,
+    warmup_runs: usize,
+    rows: Vec<&QueryDefinedBaselineComparisonRow>,
+) -> QueryDefinedBaselineMatrixSummaryRow {
+    let correctness_rate = if rows.is_empty() {
+        0.0
+    } else {
+        rows.iter()
+            .filter(|run| run.baseline.correctness_ok && run.live_only.correctness_ok)
+            .count() as f64
+            / rows.len() as f64
+    };
+
+    let baseline_rows = rows.iter().map(|comparison| &comparison.baseline).collect::<Vec<_>>();
+    let live_rows = rows.iter().map(|comparison| &comparison.live_only).collect::<Vec<_>>();
+    let first_baseline = baseline_rows.first().copied();
+    let observed_baseline_rows = rows
+        .iter()
+        .map(|comparison| comparison.observed_baseline_rows as f64)
+        .collect::<Vec<_>>();
+    let observed_live_only_rows = rows
+        .iter()
+        .map(|comparison| comparison.observed_live_only_rows as f64)
+        .collect::<Vec<_>>();
+    let observed_emitted_windows = rows
+        .iter()
+        .map(|comparison| comparison.baseline.observed_emitted_windows as f64)
+        .collect::<Vec<_>>();
+
+    let baseline_eval_ms = collect_optional_metric(&baseline_rows, |run| run.baseline_eval_ms);
+    let materialization_ms = collect_optional_metric(&baseline_rows, |run| run.materialization_ms);
+    let static_injection_ms =
+        collect_optional_metric(&baseline_rows, |run| run.static_injection_ms);
+    let historical_generation_ms =
+        collect_optional_metric(&baseline_rows, |run| run.historical_generation_ms);
+    let storage_write_ms = collect_optional_metric(&baseline_rows, |run| run.storage_write_ms);
+    let baseline_binding_count = collect_optional_metric(&baseline_rows, |run| {
+        run.baseline_binding_count.map(|value| value as f64)
+    });
+    let materialized_quad_count = collect_optional_metric(&baseline_rows, |run| {
+        run.materialized_quad_count.map(|value| value as f64)
+    });
+
+    let baseline_first_result =
+        baseline_rows.iter().map(|run| run.first_result_latency_ms).collect::<Vec<_>>();
+    let live_only_first_result =
+        live_rows.iter().map(|run| run.first_result_latency_ms).collect::<Vec<_>>();
+    let startup_overheads = rows
+        .iter()
+        .map(|comparison| comparison.live_startup_overhead_ms)
+        .collect::<Vec<_>>();
+    let first_result_overheads = rows
+        .iter()
+        .map(|comparison| comparison.first_result_overhead_ms)
+        .collect::<Vec<_>>();
+    let peak_rss_mb = rows.iter().map(|comparison| comparison.peak_rss_mb).collect::<Vec<_>>();
+    let mean_rss_mb = rows.iter().map(|comparison| comparison.mean_rss_mb).collect::<Vec<_>>();
+    let peak_cpu_percent =
+        rows.iter().map(|comparison| comparison.peak_cpu_percent).collect::<Vec<_>>();
+    let mean_cpu_percent =
+        rows.iter().map(|comparison| comparison.mean_cpu_percent).collect::<Vec<_>>();
+    let baseline_result_counts =
+        baseline_rows.iter().map(|run| run.result_count as f64).collect::<Vec<_>>();
+    let live_only_result_counts =
+        live_rows.iter().map(|run| run.result_count as f64).collect::<Vec<_>>();
+
+    let baseline_eval_stats = baseline_eval_ms.as_ref().map(|values| stats(values));
+    let materialization_stats = materialization_ms.as_ref().map(|values| stats(values));
+    let static_injection_stats = static_injection_ms.as_ref().map(|values| stats(values));
+    let baseline_binding_stats = baseline_binding_count.as_ref().map(|values| stats(values));
+    let materialized_quad_stats = materialized_quad_count.as_ref().map(|values| stats(values));
+    let peak_rss_stats = collect_optional_metric_from_rows(&peak_rss_mb);
+    let mean_rss_stats = collect_optional_metric_from_rows(&mean_rss_mb);
+    let peak_cpu_stats = collect_optional_metric_from_rows(&peak_cpu_percent);
+    let mean_cpu_stats = collect_optional_metric_from_rows(&mean_cpu_percent);
+    let expected_emitted_windows = first_baseline.map(|run| run.expected_emitted_windows as f64);
+    let expected_full_windows = first_baseline.map(|run| run.expected_full_windows as f64);
+    let warmup_window_count =
+        first_baseline.and_then(|run| run.warmup_window_count.map(|value| value as f64));
+    let observed_emitted_windows_stats = stats(&observed_emitted_windows);
+    let observed_baseline_rows_stats = stats(&observed_baseline_rows);
+    let observed_live_only_rows_stats = stats(&observed_live_only_rows);
+
+    QueryDefinedBaselineMatrixSummaryRow {
+        profile: profile.to_string(),
+        historical_events,
+        baseline_entities,
+        runs: rows.len(),
+        warmup_runs,
+        correctness_rate,
+        expected_emitted_windows,
+        expected_full_windows,
+        warmup_window_count,
+        observed_emitted_windows_mean: observed_emitted_windows_stats.mean,
+        observed_emitted_windows_std: observed_emitted_windows_stats.std,
+        observed_baseline_rows_mean: observed_baseline_rows_stats.mean,
+        observed_baseline_rows_std: observed_baseline_rows_stats.std,
+        observed_live_only_rows_mean: observed_live_only_rows_stats.mean,
+        observed_live_only_rows_std: observed_live_only_rows_stats.std,
+        historical_generation_ms_mean: historical_generation_ms
+            .as_ref()
+            .map(|values| stats(values).mean),
+        historical_generation_ms_std: historical_generation_ms
+            .as_ref()
+            .map(|values| stats(values).std),
+        storage_write_ms_mean: storage_write_ms.as_ref().map(|values| stats(values).mean),
+        storage_write_ms_std: storage_write_ms.as_ref().map(|values| stats(values).std),
+        peak_rss_mb_mean: peak_rss_stats.as_ref().map(|value| value.mean),
+        peak_rss_mb_std: peak_rss_stats.as_ref().map(|value| value.std),
+        mean_rss_mb_mean: mean_rss_stats.as_ref().map(|value| value.mean),
+        mean_rss_mb_std: mean_rss_stats.as_ref().map(|value| value.std),
+        peak_cpu_percent_mean: peak_cpu_stats.as_ref().map(|value| value.mean),
+        peak_cpu_percent_std: peak_cpu_stats.as_ref().map(|value| value.std),
+        mean_cpu_percent_mean: mean_cpu_stats.as_ref().map(|value| value.mean),
+        mean_cpu_percent_std: mean_cpu_stats.as_ref().map(|value| value.std),
+        baseline_eval_ms_mean: baseline_eval_stats.as_ref().map(|value| value.mean),
+        baseline_eval_ms_std: baseline_eval_stats.as_ref().map(|value| value.std),
+        materialization_ms_mean: materialization_stats.as_ref().map(|value| value.mean),
+        materialization_ms_std: materialization_stats.as_ref().map(|value| value.std),
+        static_injection_ms_mean: static_injection_stats.as_ref().map(|value| value.mean),
+        static_injection_ms_std: static_injection_stats.as_ref().map(|value| value.std),
+        baseline_first_result_ms_mean: stats(&baseline_first_result).mean,
+        baseline_first_result_ms_std: stats(&baseline_first_result).std,
+        live_only_first_result_ms_mean: stats(&live_only_first_result).mean,
+        live_only_first_result_ms_std: stats(&live_only_first_result).std,
+        startup_overhead_ms_mean: stats(&startup_overheads).mean,
+        startup_overhead_ms_std: stats(&startup_overheads).std,
+        first_result_overhead_ms_mean: stats(&first_result_overheads).mean,
+        first_result_overhead_ms_std: stats(&first_result_overheads).std,
+        baseline_binding_count_mean: baseline_binding_stats.as_ref().map(|value| value.mean),
+        baseline_binding_count_std: baseline_binding_stats.as_ref().map(|value| value.std),
+        materialized_quad_count_mean: materialized_quad_stats.as_ref().map(|value| value.mean),
+        materialized_quad_count_std: materialized_quad_stats.as_ref().map(|value| value.std),
+        baseline_result_count_mean: stats(&baseline_result_counts).mean,
+        baseline_result_count_std: stats(&baseline_result_counts).std,
+        live_only_result_count_mean: stats(&live_only_result_counts).mean,
+        live_only_result_count_std: stats(&live_only_result_counts).std,
+    }
+}
+
+#[derive(Clone, Copy, Debug)]
+struct MetricStats {
+    mean: f64,
+    std: f64,
+}
+
+fn stats(values: &[f64]) -> MetricStats {
+    if values.is_empty() {
+        return MetricStats { mean: 0.0, std: 0.0 };
+    }
+
+    let mean = values.iter().sum::<f64>() / values.len() as f64;
+    let std = if values.len() > 1 {
+        let variance = values
+            .iter()
+            .map(|value| {
+                let delta = value - mean;
+                delta * delta
+            })
+            .sum::<f64>()
+            / (values.len() as f64 - 1.0);
+        variance.sqrt()
+    } else {
+        0.0
+    };
+
+    MetricStats { mean, std }
+}
+
+fn collect_optional_metric<F>(
+    runs: &[&QueryDefinedBaselineVariantMetrics],
+    f: F,
+) -> Option<Vec<f64>>
+where
+    F: Fn(&QueryDefinedBaselineVariantMetrics) -> Option<f64>,
+{
+    let values = runs.iter().filter_map(|run| f(run)).collect::<Vec<_>>();
+    if values.is_empty() {
+        None
+    } else {
+        Some(values)
+    }
+}
+
+fn collect_optional_metric_from_rows(values: &[Option<f64>]) -> Option<MetricStats> {
+    let filtered = values.iter().copied().flatten().collect::<Vec<_>>();
+    if filtered.is_empty() {
+        None
+    } else {
+        Some(stats(&filtered))
+    }
+}
+
+fn summarize_resource_samples(samples: &[ResourceSample]) -> ResourceSummary {
+    if samples.is_empty() {
+        return ResourceSummary::default();
+    }
+
+    let rss_values = samples.iter().map(|sample| sample.rss_mb).collect::<Vec<_>>();
+    let cpu_values = samples.iter().map(|sample| sample.cpu_percent).collect::<Vec<_>>();
+    let rss_stats = stats(&rss_values);
+    let cpu_stats = stats(&cpu_values);
+
+    ResourceSummary {
+        peak_rss_mb: rss_values.iter().copied().reduce(f64::max),
+        mean_rss_mb: Some(rss_stats.mean),
+        peak_cpu_percent: cpu_values.iter().copied().reduce(f64::max),
+        mean_cpu_percent: Some(cpu_stats.mean),
+        sample_count: samples.len(),
+    }
+}
+
+fn write_summary_csv(
+    path: &Path,
+    rows: &QueryDefinedBaselineBenchmarkCsvRows,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let mut file = File::create(path)?;
+    writeln!(
+        file,
+        "historical_events,baseline_entities,measured_runs,warmup_runs,correctness_rate,expected_emitted_windows,expected_full_windows,warmup_window_count,observed_emitted_windows_mean,observed_emitted_windows_std,observed_baseline_rows_mean,observed_baseline_rows_std,observed_live_only_rows_mean,observed_live_only_rows_std,baseline_binding_count_mean,materialized_quad_count_mean,baseline_result_count_mean,live_only_result_count_mean,baseline_eval_ms_mean,baseline_eval_ms_std,materialization_ms_mean,materialization_ms_std,static_injection_ms_mean,static_injection_ms_std,baseline_first_result_ms_mean,baseline_first_result_ms_std,live_only_first_result_ms_mean,live_only_first_result_ms_std,startup_overhead_ms_mean,startup_overhead_ms_std,first_result_overhead_ms_mean,first_result_overhead_ms_std,historical_generation_ms_mean,historical_generation_ms_std,storage_write_ms_mean,storage_write_ms_std,peak_rss_mb_mean,peak_rss_mb_std,mean_rss_mb_mean,mean_rss_mb_std,peak_cpu_percent_mean,peak_cpu_percent_std,mean_cpu_percent_mean,mean_cpu_percent_std"
+    )?;
+
+    for row in &rows.matrix_summaries {
+        let columns = vec![
+            row.historical_events.to_string(),
+            row.baseline_entities.to_string(),
+            row.runs.to_string(),
+            row.warmup_runs.to_string(),
+            format!("{:.3}", row.correctness_rate),
+            format_opt(row.expected_emitted_windows),
+            format_opt(row.expected_full_windows),
+            format_opt(row.warmup_window_count),
+            format!("{:.3}", row.observed_emitted_windows_mean),
+            format!("{:.3}", row.observed_emitted_windows_std),
+            format!("{:.3}", row.observed_baseline_rows_mean),
+            format!("{:.3}", row.observed_baseline_rows_std),
+            format!("{:.3}", row.observed_live_only_rows_mean),
+            format!("{:.3}", row.observed_live_only_rows_std),
+            format_opt(row.baseline_binding_count_mean),
+            format_opt(row.materialized_quad_count_mean),
+            format!("{:.3}", row.baseline_result_count_mean),
+            format!("{:.3}", row.live_only_result_count_mean),
+            format_opt(row.baseline_eval_ms_mean),
+            format_opt(row.baseline_eval_ms_std),
+            format_opt(row.materialization_ms_mean),
+            format_opt(row.materialization_ms_std),
+            format_opt(row.static_injection_ms_mean),
+            format_opt(row.static_injection_ms_std),
+            format!("{:.3}", row.baseline_first_result_ms_mean),
+            format!("{:.3}", row.baseline_first_result_ms_std),
+            format!("{:.3}", row.live_only_first_result_ms_mean),
+            format!("{:.3}", row.live_only_first_result_ms_std),
+            format!("{:.3}", row.startup_overhead_ms_mean),
+            format!("{:.3}", row.startup_overhead_ms_std),
+            format!("{:.3}", row.first_result_overhead_ms_mean),
+            format!("{:.3}", row.first_result_overhead_ms_std),
+            format_opt(row.historical_generation_ms_mean),
+            format_opt(row.historical_generation_ms_std),
+            format_opt(row.storage_write_ms_mean),
+            format_opt(row.storage_write_ms_std),
+            format_opt(row.peak_rss_mb_mean),
+            format_opt(row.peak_rss_mb_std),
+            format_opt(row.mean_rss_mb_mean),
+            format_opt(row.mean_rss_mb_std),
+            format_opt(row.peak_cpu_percent_mean),
+            format_opt(row.peak_cpu_percent_std),
+            format_opt(row.mean_cpu_percent_mean),
+            format_opt(row.mean_cpu_percent_std),
+        ];
+        writeln!(file, "{}", columns.join(","))?;
+    }
+
+    Ok(())
+}
+
+fn format_opt(value: Option<f64>) -> String {
+    value.map(|v| format!("{v:.3}")).unwrap_or_default()
+}
+
+fn write_summary_markdown(
+    path: &Path,
+    rows: &QueryDefinedBaselineBenchmarkCsvRows,
+) -> Result<(), Box<dyn std::error::Error>> {
+    let mut file = File::create(path)?;
+    writeln!(file, "| historical_events | baseline_entities | expected_emitted_windows | expected_full_windows | warmup_window_count | observed_emitted_windows | observed_baseline_rows | observed_live_only_rows | injected_quads | baseline_eval_ms | materialization_ms | static_injection_ms | first_result_overhead_ms | peak_rss_mb | mean_cpu_percent | correctness_rate |")?;
+    writeln!(
+        file,
+        "| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |"
+    )?;
+
+    for row in &rows.matrix_summaries {
+        let injected_quads =
+            row.materialized_quad_count_mean.unwrap_or(row.baseline_entities as f64);
+        writeln!(
+            file,
+            "| {} | {} | {} | {} | {} | {:.3} | {:.3} | {:.3} | {} | {} | {} | {} | {} | {} | {} | {:.3} |",
+            row.historical_events,
+            row.baseline_entities,
+            format_opt(row.expected_emitted_windows),
+            format_opt(row.expected_full_windows),
+            format_opt(row.warmup_window_count),
+            row.observed_emitted_windows_mean,
+            row.observed_baseline_rows_mean,
+            row.observed_live_only_rows_mean,
+            format_decimal(injected_quads),
+            format_mean_std(row.baseline_eval_ms_mean, row.baseline_eval_ms_std),
+            format_mean_std(row.materialization_ms_mean, row.materialization_ms_std),
+            format_mean_std(row.static_injection_ms_mean, row.static_injection_ms_std),
+            format_mean_std(
+                Some(row.first_result_overhead_ms_mean),
+                Some(row.first_result_overhead_ms_std),
+            ),
+            format_mean_std(row.peak_rss_mb_mean, row.peak_rss_mb_std),
+            format_mean_std(row.mean_cpu_percent_mean, row.mean_cpu_percent_std),
+            row.correctness_rate,
+        )?;
+    }
+
+    Ok(())
+}
+
+fn format_mean_std(mean: Option<f64>, std: Option<f64>) -> String {
+    match (mean, std) {
+        (Some(mean), Some(std)) => format!("{mean:.3} ± {std:.3}"),
+        (Some(mean), None) => format!("{mean:.3} ± 0.000"),
+        (None, _) => String::new(),
+    }
+}
+
+fn format_decimal(value: f64) -> String {
+    if (value - value.round()).abs() < f64::EPSILON {
+        format!("{:.0}", value)
+    } else {
+        format!("{value:.3}")
+    }
+}
+
+fn normalize_binding_term(raw: &str) -> String {
+    let trimmed = raw.trim();
+    if trimmed.starts_with('<') && trimmed.ends_with('>') && trimmed.len() > 2 {
+        trimmed[1..trimmed.len() - 1].to_string()
+    } else if trimmed.starts_with('"') && trimmed.ends_with('"') && trimmed.len() > 2 {
+        trimmed[1..trimmed.len() - 1].to_string()
+    } else {
+        trimmed.to_string()
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn accelerated_replay() -> ResolvedLiveReplayConfig {
+        ResolvedLiveReplayConfig {
+            mode: LiveReplayMode::Accelerated,
+            rate_hz: 4.0,
+            live_duration_seconds: None,
+            live_window_size_seconds: None,
+            live_window_slide_seconds: None,
+            live_event_count: 10,
+            event_interval_ms: 0.0,
+            expected_emitted_windows: 0,
+            expected_full_windows: 0,
+            warmup_window_count: None,
+        }
+    }
+
+    fn synthetic_row(
+        sensor: &str,
+        minute: f64,
+        day: Option<f64>,
+        diff: Option<f64>,
+    ) -> QueryDefinedBaselineObservedRow {
+        QueryDefinedBaselineObservedRow {
+            sensor: sensor.to_string(),
+            minute_avg_value: minute,
+            day_avg_value: day,
+            difference: diff,
+            received_after_first_event_ms: 1.0,
+            timestamp_from: 10,
+            timestamp_to: 70,
+        }
+    }
+
+    #[test]
+    fn live_only_accelerated_mode_accepts_multiple_emitted_windows() {
+        let rows = vec![
+            synthetic_row("http://example.org/sensor0", 20.0, None, None),
+            synthetic_row("http://example.org/sensor1", 30.0, None, None),
+        ];
+        let expected_live = HashMap::from([
+            ("http://example.org/sensor0".to_string(), 20.0),
+            ("http://example.org/sensor1".to_string(), 30.0),
+        ]);
+
+        let result =
+            validate_live_only_rows(&rows, &expected_live, 2, &accelerated_replay(), 4, 2, 2);
+        assert!(result.is_ok(), "{result:?}");
+    }
+
+    #[test]
+    fn baseline_accelerated_mode_accepts_multiple_emitted_windows() {
+        let rows = vec![
+            synthetic_row("http://example.org/sensor0", 20.0, Some(10.0), Some(10.0)),
+            synthetic_row("http://example.org/sensor1", 30.0, Some(11.0), Some(19.0)),
+        ];
+        let expected_live = HashMap::from([
+            ("http://example.org/sensor0".to_string(), 20.0),
+            ("http://example.org/sensor1".to_string(), 30.0),
+        ]);
+        let expected_day = HashMap::from([
+            ("http://example.org/sensor0".to_string(), 10.0),
+            ("http://example.org/sensor1".to_string(), 11.0),
+        ]);
+
+        let result = validate_baseline_rows(
+            &rows,
+            &expected_live,
+            &expected_day,
+            2,
+            &accelerated_replay(),
+            4,
+            2,
+            2,
+        );
+        assert!(result.is_ok(), "{result:?}");
+    }
+
+    #[test]
+    fn failed_validation_builds_structured_diagnostics() {
+        let rows = vec![synthetic_row("http://example.org/sensor0", 20.0, Some(10.0), None)];
+        let expected_live = HashMap::from([("http://example.org/sensor0".to_string(), 20.0)]);
+
+        let reason =
+            validate_live_only_rows(&rows, &expected_live, 1, &accelerated_replay(), 1, 1, 1)
+                .expect_err("validation should fail");
+        let diagnostics = build_correctness_diagnostics(
+            "live_only",
+            1,
+            &rows,
+            None,
+            1,
+            vec!["sensor".to_string(), "minuteAvgValue".to_string()],
+            reason.clone(),
+        );
+
+        assert_eq!(diagnostics.variant, "live_only");
+        assert_eq!(diagnostics.expected_result_count, 1);
+        assert_eq!(diagnostics.observed_result_count, 1);
+        assert_eq!(diagnostics.reason, reason);
+        assert_eq!(diagnostics.first_observed_rows.len(), 1);
+        assert!(diagnostics.observed_variables.contains(&"dayAvgValue".to_string()));
+    }
+}
diff --git a/src/parsing/janusql_parser.rs b/src/parsing/janusql_parser.rs
index 923f49d..bab1ed2 100644
--- a/src/parsing/janusql_parser.rs
+++ b/src/parsing/janusql_parser.rs
@@ -94,6 +94,30 @@ pub struct BaselineClause {
     pub mode: BaselineBootstrapMode,
 }
 
+#[derive(Debug, Clone, PartialEq)]
+pub struct BaselineDefinition {
+    pub name: String,
+    pub source_window: String,
+    pub raw_query: String,
+    pub select_clause: String,
+    pub where_clause: String,
+    pub group_by_clause: Option<String>,
+    pub output_variables: Vec<String>,
+}
+
+#[derive(Debug, Clone, PartialEq)]
+pub struct BaselineUse {
+    pub name: String,
+}
+
+#[derive(Debug, Clone, PartialEq)]
+pub struct GeneratedBaselineQuery {
+    pub name: String,
+    pub source_window: String,
+    pub sparql_query: String,
+    pub output_variables: Vec<String>,
+}
+
 #[derive(Debug, Clone, PartialEq)]
 /// One parsed `WINDOW foo { ... }` block from the WHERE clause.
 pub struct WhereWindowClause {
@@ -101,16 +125,43 @@ pub struct WhereWindowClause {
     pub body: String,
 }
 
+#[derive(Debug, Clone, PartialEq)]
+pub enum GraphTermTemplate {
+    Variable(String),
+    Iri(String),
+    Literal(String),
+}
+
+#[derive(Debug, Clone, PartialEq)]
+pub struct TripleTemplate {
+    pub subject: GraphTermTemplate,
+    pub predicate: GraphTermTemplate,
+    pub object: GraphTermTemplate,
+}
+
+#[derive(Debug, Clone, PartialEq)]
+/// Explicit `GRAPH :baselineName { ... }` template extracted from the live query.
+pub struct BaselineGraphTemplate {
+    /// Named graph IRI for the baseline materialization target.
+    pub baseline_name: String,
+    pub triples: Vec<TripleTemplate>,
+}
+
 #[derive(Debug, Clone, PartialEq)]
 /// Abstract syntax tree for a JanusQL query.
 pub struct JanusQueryAst {
     pub prefixes: Vec<PrefixDeclaration>,
     pub register: Option<RegisterClause>,
     pub baseline: Option<BaselineClause>,
+    pub baseline_definitions: Vec<BaselineDefinition>,
+    pub baseline_uses: Vec<BaselineUse>,
     pub select_clause: String,
     pub windows: Vec<WindowClause>,
     pub where_clause: String,
     pub where_windows: Vec<WhereWindowClause>,
+    pub baseline_graph_templates: Vec<BaselineGraphTemplate>,
+    pub group_by_clause: Option<String>,
+    pub having_clause: Option<String>,
 }
 
 /// Parsed JanusQL query structure containing all components extracted from the query.
@@ -130,6 +181,14 @@ pub struct ParsedJanusQuery {
     pub rspql_query: String,
     /// SPARQL queries
     pub sparql_queries: Vec<String>,
+    /// Query-defined baseline SPARQL queries
+    pub generated_baseline_queries: Vec<GeneratedBaselineQuery>,
+    /// Explicit materialization templates extracted from `GRAPH :baselineName { ... }` blocks.
+    pub baseline_graph_templates: Vec<BaselineGraphTemplate>,
+    /// Top-level `GROUP BY` clause captured from the live query, if present.
+    pub group_by_clause: Option<String>,
+    /// Top-level `HAVING` clause captured from the live query, if present.
+    pub having_clause: Option<String>,
     /// Prefix mappings
     pub prefixes: HashMap<String, String>,
     /// WHERE clause
@@ -153,12 +212,19 @@ impl JanusQLParser {
         let mut prefix_mapper = HashMap::new();
         let mut register = None;
         let mut baseline = None;
+        let mut baseline_definitions = Vec::new();
+        let mut baseline_uses = Vec::new();
         let mut select_clause = String::new();
+        let mut main_group_by_clause = None;
+        let mut main_having_clause = None;
+        let mut in_main_select = false;
         let mut windows = Vec::new();
         let mut in_where_clause = false;
         let mut where_lines: Vec<&str> = Vec::new();
         let lines = query.lines().collect::<Vec<_>>();
         let mut index = 0;
+        let mut current_baseline_header: Option<(String, String)> = None;
+        let mut current_baseline_lines: Vec<String> = Vec::new();
 
         while index < lines.len() {
             let line = lines[index];
@@ -176,17 +242,49 @@ impl JanusQLParser {
                 continue;
             }
 
+            if current_baseline_header.is_some()
+                && (trimmed_line.starts_with("REGISTER")
+                    || trimmed_line.starts_with("DEFINE BASELINE"))
+            {
+                let (name, source_window) =
+                    current_baseline_header.take().expect("baseline header");
+                baseline_definitions.push(self.build_baseline_definition(
+                    name,
+                    source_window,
+                    &current_baseline_lines,
+                )?);
+                current_baseline_lines.clear();
+            }
+
             if trimmed_line.starts_with("REGISTER") {
+                in_where_clause = false;
+                in_main_select = false;
                 register = Some(self.parse_register_clause(trimmed_line, &prefix_mapper)?);
+            } else if trimmed_line.starts_with("DEFINE BASELINE") {
+                in_where_clause = false;
+                in_main_select = false;
+                current_baseline_header =
+                    Some(self.parse_baseline_definition_header(trimmed_line, &prefix_mapper)?);
             } else if trimmed_line.starts_with("USING BASELINE") {
-                baseline = Some(self.parse_baseline_clause(trimmed_line, &prefix_mapper)?);
+                in_where_clause = false;
+                in_main_select = false;
+                if self.is_legacy_baseline_clause(trimmed_line) {
+                    baseline = Some(self.parse_baseline_clause(trimmed_line, &prefix_mapper)?);
+                } else {
+                    baseline_uses
+                        .push(self.parse_baseline_use_clause(trimmed_line, &prefix_mapper)?);
+                }
             } else if trimmed_line.starts_with("PREFIX") {
                 let prefix = self.parse_prefix_declaration(trimmed_line)?;
                 prefix_mapper.insert(prefix.prefix.clone(), prefix.namespace.clone());
                 prefixes.push(prefix);
+            } else if current_baseline_header.is_some() {
+                current_baseline_lines.push(line.to_string());
             } else if trimmed_line.starts_with("SELECT") {
                 select_clause = trimmed_line.to_string();
+                in_main_select = true;
             } else if trimmed_line.starts_with("FROM NAMED WINDOW") {
+                in_main_select = false;
                 let mut clause = trimmed_line.to_string();
                 while !clause.contains(']') && index + 1 < lines.len() {
                     index += 1;
@@ -196,7 +294,21 @@ impl JanusQLParser {
                 windows.push(self.parse_window_clause(&clause, &prefix_mapper)?);
             } else if trimmed_line.starts_with("WHERE") {
                 in_where_clause = true;
+                in_main_select = false;
                 where_lines.push(line);
+            } else if trimmed_line.starts_with("GROUP BY") {
+                in_main_select = false;
+                if register.is_some() {
+                    main_group_by_clause = Some(trimmed_line.to_string());
+                }
+            } else if trimmed_line.starts_with("HAVING") {
+                in_main_select = false;
+                if register.is_some() {
+                    main_having_clause = Some(trimmed_line.to_string());
+                }
+            } else if in_main_select {
+                select_clause.push(' ');
+                select_clause.push_str(trimmed_line);
             } else if in_where_clause {
                 where_lines.push(line);
             }
@@ -204,17 +316,44 @@ impl JanusQLParser {
             index += 1;
         }
 
-        let where_clause = where_lines.join("\n");
+        if let Some((name, source_window)) = current_baseline_header.take() {
+            baseline_definitions.push(self.build_baseline_definition(
+                name,
+                source_window,
+                &current_baseline_lines,
+            )?);
+        }
+
+        let mut where_clause = where_lines.join("\n");
+        if let Some(group_by_clause) = &main_group_by_clause {
+            if !where_clause.is_empty() {
+                where_clause.push('\n');
+            }
+            where_clause.push_str(group_by_clause);
+        }
+        if let Some(having_clause) = &main_having_clause {
+            if !where_clause.is_empty() {
+                where_clause.push('\n');
+            }
+            where_clause.push_str(having_clause);
+        }
         let where_windows = self.extract_where_windows(&where_clause);
+        let baseline_graph_templates =
+            self.extract_baseline_graph_templates(&where_clause, &prefix_mapper)?;
 
         Ok(JanusQueryAst {
             prefixes,
             register,
             baseline,
+            baseline_definitions,
+            baseline_uses,
             select_clause,
             windows,
             where_clause,
             where_windows,
+            baseline_graph_templates,
+            group_by_clause: main_group_by_clause,
+            having_clause: main_having_clause,
         })
     }
 
@@ -262,6 +401,44 @@ impl JanusQLParser {
             }
         }
 
+        let window_map = ast
+            .windows
+            .iter()
+            .map(|window| (window.window_name.clone(), window))
+            .collect::<HashMap<_, _>>();
+
+        for definition in &ast.baseline_definitions {
+            let Some(source_window) = window_map.get(&definition.source_window) else {
+                return Err(self.parse_error(format!(
+                    "DEFINE BASELINE references unknown source window '{}'",
+                    definition.source_window
+                )));
+            };
+
+            let lowered = self.lower_window_clause(source_window);
+            if source_window.source_kind != SourceKind::Log
+                || lowered.window_type == WindowType::Live
+            {
+                return Err(self.parse_error(format!(
+                    "DEFINE BASELINE source window '{}' must be a historical LOG window",
+                    definition.source_window
+                )));
+            }
+        }
+
+        for baseline_use in &ast.baseline_uses {
+            let exists = ast
+                .baseline_definitions
+                .iter()
+                .any(|definition| definition.name == baseline_use.name);
+            if !exists {
+                return Err(self.parse_error(format!(
+                    "USING BASELINE references undefined baseline '{}'",
+                    baseline_use.name
+                )));
+            }
+        }
+
         let mut parsed = ParsedJanusQuery {
             ast: ast.clone(),
             baseline: ast.baseline.clone(),
@@ -270,6 +447,10 @@ impl JanusQLParser {
             historical_windows,
             rspql_query: String::new(),
             sparql_queries: Vec::new(),
+            generated_baseline_queries: Vec::new(),
+            baseline_graph_templates: ast.baseline_graph_templates.clone(),
+            group_by_clause: ast.group_by_clause.clone(),
+            having_clause: ast.having_clause.clone(),
             prefixes,
             where_clause: ast.where_clause.clone(),
             select_clause: ast.select_clause.clone(),
@@ -279,10 +460,17 @@ impl JanusQLParser {
             parsed.rspql_query = self.generate_rspql_query(&parsed, &prefix_lines);
         }
         parsed.sparql_queries = self.generate_sparql_queries(&parsed, &prefix_lines);
+        parsed.generated_baseline_queries =
+            self.generate_baseline_queries(&parsed.ast.baseline_definitions, &prefix_lines);
 
         Ok(parsed)
     }
 
+    fn is_legacy_baseline_clause(&self, line: &str) -> bool {
+        let parts = line.split_whitespace().collect::<Vec<_>>();
+        parts.len() == 4 && parts[0] == "USING" && parts[1] == "BASELINE"
+    }
+
     fn parse_baseline_clause(
         &self,
         line: &str,
@@ -306,6 +494,98 @@ impl JanusQLParser {
         Ok(BaselineClause { window_name: self.unwrap_iri(parts[2], prefix_mapper), mode })
     }
 
+    fn parse_baseline_use_clause(
+        &self,
+        line: &str,
+        prefix_mapper: &HashMap<String, String>,
+    ) -> Result<BaselineUse, Box<dyn std::error::Error>> {
+        let parts = line.split_whitespace().collect::<Vec<_>>();
+        if parts.len() != 3 || parts[0] != "USING" || parts[1] != "BASELINE" {
+            return Err(self.parse_error(format!("Invalid USING BASELINE clause: {line}")));
+        }
+
+        Ok(BaselineUse { name: self.unwrap_iri(parts[2], prefix_mapper) })
+    }
+
+    fn parse_baseline_definition_header(
+        &self,
+        line: &str,
+        prefix_mapper: &HashMap<String, String>,
+    ) -> Result<(String, String), Box<dyn std::error::Error>> {
+        let parts = line.split_whitespace().collect::<Vec<_>>();
+        if parts.len() != 7
+            || parts[0] != "DEFINE"
+            || parts[1] != "BASELINE"
+            || parts[3] != "ON"
+            || parts[4] != "WINDOW"
+            || parts[6] != "AS"
+        {
+            return Err(self.parse_error(format!("Invalid DEFINE BASELINE clause: {line}")));
+        }
+
+        Ok((
+            self.unwrap_iri(parts[2], prefix_mapper),
+            self.unwrap_iri(parts[5], prefix_mapper),
+        ))
+    }
+
+    fn build_baseline_definition(
+        &self,
+        name: String,
+        source_window: String,
+        raw_lines: &[String],
+    ) -> Result<BaselineDefinition, Box<dyn std::error::Error>> {
+        let raw_query = raw_lines.join("\n").trim().to_string();
+        if raw_query.is_empty() {
+            return Err(
+                self.parse_error(format!("DEFINE BASELINE '{}' must include a SELECT query", name))
+            );
+        }
+
+        let mut select_clause = String::new();
+        let mut where_lines = Vec::new();
+        let mut group_by_clause = None;
+        let mut in_where = false;
+
+        for line in raw_query.lines().map(str::to_string).collect::<Vec<_>>() {
+            let trimmed = line.trim();
+            if trimmed.starts_with("SELECT") {
+                select_clause = trimmed.to_string();
+                in_where = false;
+            } else if trimmed.starts_with("WHERE") {
+                in_where = true;
+                where_lines.push(line);
+            } else if trimmed.starts_with("GROUP BY") {
+                group_by_clause = Some(trimmed.to_string());
+                in_where = false;
+            } else if in_where {
+                where_lines.push(line);
+            } else if !select_clause.is_empty() {
+                select_clause.push(' ');
+                select_clause.push_str(trimmed);
+            }
+        }
+
+        if select_clause.is_empty() || where_lines.is_empty() {
+            return Err(self.parse_error(format!(
+                "DEFINE BASELINE '{}' must include SELECT and WHERE clauses",
+                name
+            )));
+        }
+
+        let output_variables = self.extract_output_variables(&select_clause);
+
+        Ok(BaselineDefinition {
+            name,
+            source_window,
+            raw_query,
+            select_clause,
+            where_clause: where_lines.join("\n"),
+            group_by_clause,
+            output_variables,
+        })
+    }
+
     fn parse_register_clause(
         &self,
         line: &str,
@@ -490,6 +770,14 @@ impl JanusQLParser {
             lines.push(adapted_where);
         }
 
+        if let Some(group_by_clause) = &parsed.group_by_clause {
+            lines.push(group_by_clause.clone());
+        }
+
+        if let Some(having_clause) = &parsed.having_clause {
+            lines.push(having_clause.clone());
+        }
+
         lines.join("\n")
     }
 
@@ -509,6 +797,13 @@ impl JanusQLParser {
 
             lines.push(String::new());
 
+            if self
+                .find_window_body(&parsed.ast.where_windows, window, &parsed.prefixes)
+                .is_none()
+            {
+                continue;
+            }
+
             let (where_clause, bound_vars) = self.generate_where_and_extract_vars(
                 &parsed.ast.where_windows,
                 &parsed.where_clause,
@@ -529,6 +824,38 @@ impl JanusQLParser {
         queries
     }
 
+    fn generate_baseline_queries(
+        &self,
+        baseline_definitions: &[BaselineDefinition],
+        prefix_lines: &[String],
+    ) -> Vec<GeneratedBaselineQuery> {
+        baseline_definitions
+            .iter()
+            .map(|definition| {
+                let mut lines = prefix_lines.to_vec();
+                lines.push(String::new());
+                lines.push(definition.select_clause.clone());
+                lines.push(String::new());
+                lines.push(self.wrap_baseline_where_clause(&definition.where_clause));
+                if let Some(group_by_clause) = &definition.group_by_clause {
+                    lines.push(group_by_clause.clone());
+                }
+
+                GeneratedBaselineQuery {
+                    name: definition.name.clone(),
+                    source_window: definition.source_window.clone(),
+                    sparql_query: lines.join("\n"),
+                    output_variables: definition.output_variables.clone(),
+                }
+            })
+            .collect()
+    }
+
+    fn wrap_baseline_where_clause(&self, where_clause: &str) -> String {
+        let inner = self.extract_where_inner(where_clause);
+        format!("WHERE {{\n  GRAPH ?__janus_log_graph {{\n    {}\n  }}\n}}", inner)
+    }
+
     fn generate_where_and_extract_vars(
         &self,
         where_windows: &[WhereWindowClause],
@@ -696,9 +1023,7 @@ impl JanusQLParser {
 
         if without_where.starts_with('{') {
             if let Some(end) = self.find_matching_brace(without_where, 0) {
-                if end == without_where.len() - 1 {
-                    return without_where[1..end].trim().to_string();
-                }
+                return without_where[1..end].trim().to_string();
             }
         }
 
@@ -780,6 +1105,232 @@ impl JanusQLParser {
         clauses
     }
 
+    fn extract_baseline_graph_templates(
+        &self,
+        where_clause: &str,
+        prefix_mapper: &HashMap<String, String>,
+    ) -> Result<Vec<BaselineGraphTemplate>, Box<dyn std::error::Error>> {
+        let inner = self.extract_where_inner(where_clause);
+        if inner.is_empty() {
+            return Ok(Vec::new());
+        }
+
+        let mut templates = Vec::new();
+        let mut offset = 0usize;
+
+        while let Some(found) = inner[offset..].find("GRAPH") {
+            let start = offset + found;
+            let after_keyword = start + "GRAPH".len();
+            let mut cursor = after_keyword;
+
+            while let Some(ch) = inner[cursor..].chars().next() {
+                if ch.is_whitespace() {
+                    cursor += ch.len_utf8();
+                } else {
+                    break;
+                }
+            }
+
+            let identifier_start = cursor;
+            while let Some(ch) = inner[cursor..].chars().next() {
+                if ch.is_whitespace() || ch == '{' {
+                    break;
+                }
+                cursor += ch.len_utf8();
+            }
+
+            let identifier = inner[identifier_start..cursor].trim();
+            while let Some(ch) = inner[cursor..].chars().next() {
+                if ch.is_whitespace() {
+                    cursor += ch.len_utf8();
+                } else {
+                    break;
+                }
+            }
+
+            if !inner[cursor..].starts_with('{') {
+                offset = cursor;
+                continue;
+            }
+
+            let body_start = cursor + 1;
+            let Some(body_end) = self.find_matching_brace(&inner, cursor) else {
+                return Err(self.parse_error("Unclosed GRAPH block in WHERE clause"));
+            };
+
+            let baseline_name = self.unwrap_iri(identifier, prefix_mapper);
+            let triples =
+                self.parse_graph_template_body(inner[body_start..body_end].trim(), prefix_mapper)?;
+            templates.push(BaselineGraphTemplate { baseline_name, triples });
+            offset = body_end + 1;
+        }
+
+        Ok(templates)
+    }
+
+    fn parse_graph_template_body(
+        &self,
+        body: &str,
+        prefix_mapper: &HashMap<String, String>,
+    ) -> Result<Vec<TripleTemplate>, Box<dyn std::error::Error>> {
+        let statements = self.split_graph_template_statements(body);
+        let mut triples = Vec::new();
+
+        for statement in statements {
+            let tokens = self.tokenize_graph_template_statement(&statement);
+            if tokens.is_empty() {
+                continue;
+            }
+            if tokens.len() != 3 {
+                return Err(self.parse_error(format!(
+                    "GRAPH template triple pattern must contain exactly 3 terms: {statement}"
+                )));
+            }
+
+            triples.push(TripleTemplate {
+                subject: self.parse_graph_term_template(&tokens[0], prefix_mapper),
+                predicate: self.parse_graph_term_template(&tokens[1], prefix_mapper),
+                object: self.parse_graph_term_template(&tokens[2], prefix_mapper),
+            });
+        }
+
+        Ok(triples)
+    }
+
+    fn split_graph_template_statements(&self, body: &str) -> Vec<String> {
+        let mut statements = Vec::new();
+        let chars = body.chars().collect::<Vec<_>>();
+        let mut current = String::new();
+        let mut in_string = false;
+        let mut in_iri = false;
+        let mut escaped = false;
+
+        for ch in chars {
+            if in_string {
+                current.push(ch);
+                if escaped {
+                    escaped = false;
+                } else if ch == '\\' {
+                    escaped = true;
+                } else if ch == '"' {
+                    in_string = false;
+                }
+                continue;
+            }
+
+            if in_iri {
+                current.push(ch);
+                if ch == '>' {
+                    in_iri = false;
+                }
+                continue;
+            }
+
+            match ch {
+                '"' => {
+                    in_string = true;
+                    current.push(ch);
+                }
+                '<' => {
+                    in_iri = true;
+                    current.push(ch);
+                }
+                '.' => {
+                    let trimmed = current.trim();
+                    if !trimmed.is_empty() {
+                        statements.push(trimmed.to_string());
+                    }
+                    current.clear();
+                }
+                _ => current.push(ch),
+            }
+        }
+
+        let trimmed = current.trim();
+        if !trimmed.is_empty() {
+            statements.push(trimmed.to_string());
+        }
+
+        statements
+    }
+
+    fn tokenize_graph_template_statement(&self, statement: &str) -> Vec<String> {
+        let chars = statement.chars().collect::<Vec<_>>();
+        let mut tokens = Vec::new();
+        let mut current = String::new();
+        let mut index = 0usize;
+        let mut in_string = false;
+        let mut in_iri = false;
+        let mut escaped = false;
+
+        while index < chars.len() {
+            let ch = chars[index];
+
+            if in_string {
+                current.push(ch);
+                if escaped {
+                    escaped = false;
+                } else if ch == '\\' {
+                    escaped = true;
+                } else if ch == '"' {
+                    in_string = false;
+                }
+                index += 1;
+                continue;
+            }
+
+            if in_iri {
+                current.push(ch);
+                if ch == '>' {
+                    in_iri = false;
+                }
+                index += 1;
+                continue;
+            }
+
+            match ch {
+                '"' => {
+                    in_string = true;
+                    current.push(ch);
+                }
+                '<' => {
+                    in_iri = true;
+                    current.push(ch);
+                }
+                c if c.is_whitespace() => {
+                    if !current.is_empty() {
+                        tokens.push(current.clone());
+                        current.clear();
+                    }
+                }
+                _ => current.push(ch),
+            }
+
+            index += 1;
+        }
+
+        if !current.is_empty() {
+            tokens.push(current);
+        }
+
+        tokens
+    }
+
+    fn parse_graph_term_template(
+        &self,
+        token: &str,
+        prefix_mapper: &HashMap<String, String>,
+    ) -> GraphTermTemplate {
+        let trimmed = token.trim();
+        if trimmed.starts_with('?') {
+            return GraphTermTemplate::Variable(trimmed.trim_start_matches('?').to_string());
+        }
+        if trimmed.starts_with('"') {
+            return GraphTermTemplate::Literal(trimmed.to_string());
+        }
+        GraphTermTemplate::Iri(self.unwrap_iri(trimmed, prefix_mapper))
+    }
+
     fn find_matching_brace(&self, input: &str, open_brace_index: usize) -> Option<usize> {
         let mut depth = 0usize;
         for (relative_index, ch) in input[open_brace_index..].char_indices() {
@@ -866,6 +1417,33 @@ impl JanusQLParser {
         items
     }
 
+    fn extract_output_variables(&self, select_clause: &str) -> Vec<String> {
+        let trimmed = select_clause.trim();
+        let content = trimmed
+            .strip_prefix("SELECT")
+            .or_else(|| trimmed.strip_prefix("select"))
+            .map_or(trimmed, str::trim);
+
+        self.extract_projection_items(content)
+            .into_iter()
+            .filter_map(|item| {
+                let trimmed_item = item.trim();
+                if trimmed_item.starts_with('?') {
+                    Some(trimmed_item.to_string())
+                } else if let Some(as_pos) = trimmed_item.rfind(" AS ") {
+                    let alias = trimmed_item[as_pos + 4..].trim().trim_end_matches(')').trim();
+                    if alias.starts_with('?') {
+                        Some(alias.to_string())
+                    } else {
+                        None
+                    }
+                } else {
+                    None
+                }
+            })
+            .collect()
+    }
+
     fn local_name<'a>(&self, iri: &'a str) -> Option<&'a str> {
         iri.rsplit(['#', '/']).next().filter(|local| !local.is_empty())
     }
diff --git a/src/storage/segmented_storage.rs b/src/storage/segmented_storage.rs
index 101c3a2..3eb0738 100644
--- a/src/storage/segmented_storage.rs
+++ b/src/storage/segmented_storage.rs
@@ -37,19 +37,14 @@ impl StreamingSegmentedStorage {
         // Load or create dictionary
         let dict_path = std::path::Path::new(&config.segment_base_path).join("dictionary.bin");
         let dictionary = if dict_path.exists() {
-            println!("Loading existing dictionary from {:?}", dict_path);
             match Dictionary::load_from_file(&dict_path) {
-                Ok(dict) => {
-                    println!("✓ Dictionary loaded with {} entries", dict.size());
-                    dict
-                }
+                Ok(dict) => dict,
                 Err(e) => {
                     eprintln!("Warning: Failed to load dictionary: {}, creating new one", e);
                     Dictionary::new()
                 }
             }
         } else {
-            println!("Creating new dictionary");
             Dictionary::new()
         };
 
diff --git a/src/stream/live_stream_processing.rs b/src/stream/live_stream_processing.rs
index a631201..5a2b59c 100644
--- a/src/stream/live_stream_processing.rs
+++ b/src/stream/live_stream_processing.rs
@@ -272,9 +272,14 @@ impl LiveStreamProcessing {
     /// * `event` - RDFEvent representing static knowledge
     pub fn add_static_data(&mut self, event: RDFEvent) -> Result<(), LiveStreamProcessingError> {
         let quad = self.rdf_event_to_quad(&event)?;
+        self.add_static_quad(quad);
+        Ok(())
+    }
+
+    /// Adds a pre-built static quad to the RSP engine.
+    pub fn add_static_quad(&mut self, quad: Quad) {
         self.engine.add_static_data(quad.clone());
         self.static_data.lock().unwrap().insert(quad);
-        Ok(())
     }
 
     /// Receives the next query result from the processing engine
@@ -529,7 +534,11 @@ impl LiveStreamProcessing {
         }
 
         let parsed_query = build_evaluator().parse_query(query).map_err(|e| {
-            LiveStreamProcessingError(format!("Failed to parse live SPARQL: {}", e))
+            LiveStreamProcessingError(format!(
+                "Failed to parse live SPARQL: {}\nLowered live query with line numbers:\n{}",
+                e,
+                Self::format_query_with_line_numbers(query)
+            ))
         })?;
         let results = parsed_query.on_store(&store).execute().map_err(|e| {
             LiveStreamProcessingError(format!("Failed to execute live SPARQL: {}", e))
@@ -560,6 +569,20 @@ impl LiveStreamProcessing {
     pub fn is_processing(&self) -> bool {
         self.processing_started
     }
+
+    #[cfg(test)]
+    pub fn static_quads(&self) -> HashSet<Quad> {
+        self.static_data.lock().unwrap().clone()
+    }
+
+    fn format_query_with_line_numbers(query: &str) -> String {
+        query
+            .lines()
+            .enumerate()
+            .map(|(index, line)| format!("{:>4} | {}", index + 1, line))
+            .collect::<Vec<_>>()
+            .join("\n")
+    }
 }
 
 #[cfg(test)]
diff --git a/src/stream/mqtt_subscriber.rs b/src/stream/mqtt_subscriber.rs
index a42fb62..a18220b 100644
--- a/src/stream/mqtt_subscriber.rs
+++ b/src/stream/mqtt_subscriber.rs
@@ -16,7 +16,6 @@ use std::{
     },
     time::{Duration, SystemTime, UNIX_EPOCH},
 };
-use tokio::runtime::Runtime;
 
 /// Configuration for MQTT subscriber
 #[derive(Debug, Clone)]
@@ -47,7 +46,6 @@ impl Default for MqttSubscriberConfig {
 /// MQTT Subscriber that feeds events to live query processor
 pub struct MqttSubscriber {
     config: MqttSubscriberConfig,
-    runtime: Arc<Runtime>,
     should_stop: Arc<AtomicBool>,
     events_received: Arc<Mutex<u64>>,
     errors: Arc<Mutex<u64>>,
@@ -79,17 +77,8 @@ impl std::error::Error for MqttSubscriberError {}
 impl MqttSubscriber {
     /// Create a new MQTT subscriber
     pub fn new(config: MqttSubscriberConfig) -> Self {
-        let runtime = Arc::new(
-            tokio::runtime::Builder::new_multi_thread()
-                .worker_threads(2)
-                .enable_all()
-                .build()
-                .expect("Failed to create Tokio runtime"),
-        );
-
         Self {
             config,
-            runtime,
             should_stop: Arc::new(AtomicBool::new(false)),
             events_received: Arc::new(Mutex::new(0)),
             errors: Arc::new(Mutex::new(0)),
@@ -112,7 +101,13 @@ impl MqttSubscriber {
         let events_received = Arc::clone(&self.events_received);
         let errors = Arc::clone(&self.errors);
 
-        self.runtime.block_on(async move {
+        let runtime = tokio::runtime::Builder::new_multi_thread()
+            .worker_threads(2)
+            .enable_all()
+            .build()
+            .map_err(|e| MqttSubscriberError::RuntimeError(e.to_string()))?;
+
+        runtime.block_on(async move {
             let mut mqttoptions = MqttOptions::new(&config.client_id, &config.host, config.port);
             mqttoptions.set_keep_alive(Duration::from_secs(config.keep_alive_secs));
 
diff --git a/tests/http_server_integration_test.rs b/tests/http_server_integration_test.rs
index 2001ba1..2c855ef 100644
--- a/tests/http_server_integration_test.rs
+++ b/tests/http_server_integration_test.rs
@@ -359,6 +359,58 @@ async fn test_stop_route_stops_running_query_and_delete_requires_stop() {
     assert!(delete_response.status().is_success());
 }
 
+#[tokio::test]
+async fn test_replay_completion_clears_stream_bus_for_safe_shutdown() {
+    let server = spawn_test_server().await;
+    let replay_file = server.storage_dir.join("replay_input.nq");
+    fs::write(
+        &replay_file,
+        "<http://example.org/sensor1> <http://example.org/temperature> \"24.5\" <http://example.org/graph1> .\n",
+    )
+    .expect("failed to write replay input");
+
+    let start_response = server
+        .client
+        .post(format!("{}/api/replay/start", server.base_url))
+        .json(&json!({
+            "input_file": replay_file.to_string_lossy().to_string(),
+            "broker_type": "none",
+            "topics": ["sensors"],
+            "rate_of_publishing": 0,
+            "loop_file": false,
+            "add_timestamps": true
+        }))
+        .send()
+        .await
+        .expect("replay start request failed");
+    assert!(start_response.status().is_success());
+
+    let mut completed = false;
+    for _ in 0..40 {
+        let response = server
+            .client
+            .get(format!("{}/api/replay/status", server.base_url))
+            .send()
+            .await
+            .expect("replay status request failed");
+        assert!(response.status().is_success());
+        let body: Value = response.json().await.expect("invalid replay status response");
+        if body["is_running"] == Value::Bool(false) {
+            assert_eq!(body["events_read"], 1);
+            assert_eq!(body["events_stored"], 1);
+            completed = true;
+            break;
+        }
+        sleep(Duration::from_millis(50)).await;
+    }
+
+    assert!(completed, "replay should complete for a one-line input file");
+    assert!(
+        server.state.replay_state.lock().unwrap().stream_bus.is_none(),
+        "replay state should release the stream bus once replay completes"
+    );
+}
+
 #[tokio::test]
 async fn test_results_websocket_requires_running_query() {
     let server = spawn_test_server().await;
diff --git a/tests/janus_api_integration_test.rs b/tests/janus_api_integration_test.rs
index ad6db96..2e4c1a6 100644
--- a/tests/janus_api_integration_test.rs
+++ b/tests/janus_api_integration_test.rs
@@ -3,7 +3,7 @@
 //! Tests the complete flow of registering and executing JanusQL queries
 //! with both historical and live processing.
 
-use janus::api::janus_api::{JanusApi, ResultSource};
+use janus::api::janus_api::{ExecutionStatus, JanusApi, ResultSource};
 use janus::parsing::janusql_parser::JanusQLParser;
 use janus::registry::query_registry::QueryRegistry;
 use janus::storage::segmented_storage::StreamingSegmentedStorage;
@@ -29,10 +29,7 @@ fn create_test_storage_with_data() -> Result<Arc<StreamingSegmentedStorage>, std
         entries_per_index_block: 100,
     };
 
-    let mut storage = StreamingSegmentedStorage::new(config)?;
-
-    // Start background flushing
-    storage.start_background_flushing();
+    let storage = StreamingSegmentedStorage::new(config)?;
 
     // Add some test data (timestamps from 100 to 5000 ms)
     for i in 1..=50 {
@@ -42,12 +39,11 @@ fn create_test_storage_with_data() -> Result<Arc<StreamingSegmentedStorage>, std
             &format!("http://example.org/sensor{}", i % 5),
             "http://example.org/temperature",
             &format!("{}", 20 + (i % 10)),
-            "http://example.org/graph1",
+            "http://example.org/sensors",
         )?;
     }
 
-    // Wait for background flush to complete
-    std::thread::sleep(Duration::from_secs(2));
+    storage.flush()?;
 
     Ok(Arc::new(storage))
 }
@@ -171,14 +167,11 @@ fn test_historical_fixed_window_query() {
 
     println!("Total results received: {}", results.len());
 
-    // Note: Historical queries may not return results if storage hasn't flushed yet
-    // This is a known limitation of the current test setup
-    if results.is_empty() {
-        println!("WARNING: No historical results received - storage may not have flushed data yet");
-        println!("This test is expected to pass once storage flushing is more reliable");
-        // Don't fail the test - it's a test infrastructure issue, not API issue
-        return;
-    }
+    assert!(!results.is_empty(), "Historical query should emit at least one result");
+    assert!(
+        results.iter().any(|result| !result.bindings.is_empty()),
+        "Historical query should return at least one binding"
+    );
 
     // Verify all results are historical
     for result in &results {
@@ -680,3 +673,166 @@ WHERE {
     // At least one type should have results (depending on timing and data)
     // This verifies both threads can execute concurrently
 }
+
+#[test]
+fn test_registered_query_exposes_query_defined_baseline_lowering() {
+    let parser = JanusQLParser::new().expect("Failed to create parser");
+    let registry = Arc::new(QueryRegistry::new());
+    let storage = Arc::new(
+        StreamingSegmentedStorage::new(StreamingConfig::default())
+            .expect("Failed to create storage"),
+    );
+    let api = JanusApi::new(parser, registry, storage).expect("Failed to create API");
+
+    let janusql = r#"
+PREFIX ex: <http://example.org/>
+
+FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60000 STEP 1000]
+FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [START 0 END 86400000]
+
+DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+       (COUNT(?value) AS ?dayCount)
+WHERE {
+  ?sensor ex:hasValue ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream ex:output AS
+USING BASELINE ex:dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {
+  WINDOW ex:liveMinute {
+    ?sensor ex:hasValue ?value .
+  }
+  GRAPH ex:dayBaseline {
+    ?sensor ex:dayAvgValue ?dayAvgValue .
+    ?sensor ex:dayCount ?dayCount .
+  }
+}
+GROUP BY ?sensor ?dayAvgValue
+HAVING(AVG(?value) > ?dayAvgValue)
+    "#;
+
+    let metadata = api
+        .register_query("baseline_lowering".into(), janusql)
+        .expect("Failed to register query");
+
+    assert_eq!(metadata.parsed.generated_baseline_queries.len(), 1);
+    assert_eq!(
+        metadata.parsed.generated_baseline_queries[0].name,
+        "http://example.org/dayBaseline"
+    );
+    assert!(metadata.parsed.generated_baseline_queries[0].sparql_query.contains("AVG"));
+    assert!(metadata.parsed.generated_baseline_queries[0].sparql_query.contains("COUNT"));
+    assert!(metadata.parsed.generated_baseline_queries[0].sparql_query.contains("GROUP BY"));
+    assert!(metadata.parsed.generated_baseline_queries[0]
+        .sparql_query
+        .contains("GRAPH ?__janus_log_graph"));
+    assert_eq!(metadata.parsed.ast.baseline_uses.len(), 1);
+    assert_eq!(metadata.parsed.ast.baseline_uses[0].name, "http://example.org/dayBaseline");
+    assert!(metadata.parsed.select_clause.contains("?difference"));
+    assert!(!metadata.parsed.where_clause.contains("DEFINE BASELINE"));
+    assert!(metadata.parsed.where_clause.contains("GRAPH ex:dayBaseline"));
+    assert_eq!(metadata.parsed.baseline_graph_templates.len(), 1);
+    assert_eq!(metadata.parsed.baseline_graph_templates[0].triples.len(), 2);
+}
+
+#[test]
+fn test_query_defined_baseline_live_query_starts_when_graph_is_present() {
+    let storage = create_test_storage_with_data().expect("Failed to create storage");
+    let parser = JanusQLParser::new().expect("Failed to create parser");
+    let registry = Arc::new(QueryRegistry::new());
+    let api = JanusApi::new(parser, registry, storage).expect("Failed to create API");
+
+    let janusql = r#"
+PREFIX ex: <http://example.org/>
+
+FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60000 STEP 1000]
+FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [START 0 END 86400000]
+
+DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor ex:temperature ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream ex:output AS
+USING BASELINE ex:dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+       ?dayAvgValue
+       ((AVG(?value) - ?dayAvgValue) AS ?difference)
+WHERE {
+  WINDOW ex:liveMinute {
+    ?sensor ex:temperature ?value .
+  }
+  GRAPH ex:dayBaseline {
+    ?sensor ex:dayAvgValue ?dayAvgValue .
+  }
+}
+GROUP BY ?sensor ?dayAvgValue
+    "#;
+
+    api.register_query("baseline_e2e".into(), janusql)
+        .expect("Failed to register query");
+
+    let _handle = api
+        .start_query(&"baseline_e2e".into())
+        .expect("query-defined baseline live query should start");
+
+    let bindings = api
+        .get_query_defined_baseline_bindings(&"baseline_e2e".into())
+        .expect("query-defined baseline bindings should be available after start");
+    assert!(bindings.contains_key("http://example.org/dayBaseline"));
+    assert_eq!(api.get_query_status(&"baseline_e2e".into()), Some(ExecutionStatus::Running));
+}
+
+#[test]
+fn test_query_defined_baseline_live_query_rejects_missing_graph_reference() {
+    let storage = create_test_storage_with_data().expect("Failed to create storage");
+    let parser = JanusQLParser::new().expect("Failed to create parser");
+    let registry = Arc::new(QueryRegistry::new());
+    let api = JanusApi::new(parser, registry, storage).expect("Failed to create API");
+
+    let janusql = r#"
+PREFIX ex: <http://example.org/>
+
+FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [START 0 END 6000]
+
+DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+SELECT ?sensor
+       (AVG(?value) AS ?dayAvgValue)
+WHERE {
+  ?sensor ex:temperature ?value .
+}
+GROUP BY ?sensor
+
+REGISTER RStream ex:output AS
+USING BASELINE ex:dayBaseline
+SELECT ?sensor
+       (AVG(?value) AS ?minuteAvgValue)
+WHERE {
+  WINDOW ex:liveMinute {
+    ?sensor ex:temperature ?value .
+  }
+}
+GROUP BY ?sensor
+    "#;
+
+    api.register_query("baseline_missing_graph".into(), janusql)
+        .expect("Failed to register query");
+
+    let err = match api.start_query(&"baseline_missing_graph".into()) {
+        Ok(_) => panic!("query should fail without baseline GRAPH reference"),
+        Err(err) => err,
+    };
+    assert!(err.to_string().contains("requires a matching GRAPH reference"));
+}
diff --git a/tests/janusql_parser_test.rs b/tests/janusql_parser_test.rs
index a48570b..fcc4a80 100644
--- a/tests/janusql_parser_test.rs
+++ b/tests/janusql_parser_test.rs
@@ -4,7 +4,7 @@
 //! R2S operators, and query generation.
 
 use janus::parsing::janusql_parser::{
-    BaselineBootstrapMode, JanusQLParser, SourceKind, WindowSpec,
+    BaselineBootstrapMode, GraphTermTemplate, JanusQLParser, SourceKind, WindowSpec,
 };
 
 #[test]
@@ -288,3 +288,294 @@ fn test_using_baseline_requires_known_historical_window() {
     let result = parser.parse(query);
     assert!(result.is_err());
 }
+
+#[test]
+fn parse_define_baseline_with_avg_count() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor
+               (AVG(?value) AS ?dayAvgValue)
+               (COUNT(?value) AS ?dayCount)
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        SELECT ?sensor ?dayAvgValue
+        WHERE {
+          WINDOW ex:liveMinute {
+            ?sensor ex:hasValue ?value .
+          }
+        }
+        GROUP BY ?sensor ?dayAvgValue
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert_eq!(parsed.ast.baseline_definitions.len(), 1);
+    let definition = &parsed.ast.baseline_definitions[0];
+    assert_eq!(definition.name, "http://example.org/dayBaseline");
+    assert_eq!(definition.source_window, "http://example.org/historyDay");
+    assert_eq!(definition.output_variables, vec!["?sensor", "?dayAvgValue", "?dayCount"]);
+    assert_eq!(parsed.baseline_graph_templates.len(), 0);
+    assert_eq!(parsed.generated_baseline_queries.len(), 1);
+}
+
+#[test]
+fn baseline_select_does_not_override_main_select() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor (AVG(?value) AS ?dayAvgValue)
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        SELECT ?sensor (AVG(?value) AS ?minuteAvgValue) ?dayAvgValue
+        WHERE {
+          WINDOW ex:liveMinute {
+            ?sensor ex:hasValue ?value .
+          }
+        }
+        GROUP BY ?sensor ?dayAvgValue
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert!(parsed.select_clause.contains("?minuteAvgValue"));
+    assert!(!parsed.select_clause.contains("?dayCount"));
+    assert_eq!(
+        parsed.ast.baseline_definitions[0].select_clause,
+        "SELECT ?sensor (AVG(?value) AS ?dayAvgValue)"
+    );
+}
+
+#[test]
+fn using_baseline_is_parsed_after_register() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        USING BASELINE ex:weekBaseline
+        SELECT ?sensor
+        WHERE {
+          WINDOW ex:liveMinute {
+            ?sensor ex:hasValue ?value .
+          }
+        }
+    "#;
+
+    let result = parser.parse(query);
+    assert!(result.is_err());
+
+    let query = query.replace(
+        "DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS\n        SELECT ?sensor\n        WHERE {\n          ?sensor ex:hasValue ?value .\n        }\n        GROUP BY ?sensor",
+        "DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS\n        SELECT ?sensor\n        WHERE {\n          ?sensor ex:hasValue ?value .\n        }\n        GROUP BY ?sensor\n        DEFINE BASELINE ex:weekBaseline ON WINDOW ex:historyDay AS\n        SELECT ?sensor\n        WHERE {\n          ?sensor ex:hasValue ?value .\n        }\n        GROUP BY ?sensor",
+    );
+    let parsed = parser.parse(&query).unwrap();
+    assert_eq!(parsed.ast.baseline_uses.len(), 2);
+    assert_eq!(parsed.ast.baseline_uses[0].name, "http://example.org/dayBaseline");
+    assert_eq!(parsed.ast.baseline_uses[1].name, "http://example.org/weekBaseline");
+}
+
+#[test]
+fn generated_baseline_query_wraps_where_body_in_log_graph() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor (AVG(?value) AS ?dayAvgValue) (COUNT(?value) AS ?dayCount)
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        SELECT ?sensor
+        WHERE { }
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    let generated = &parsed.generated_baseline_queries[0];
+    assert!(generated.sparql_query.contains("GRAPH ?__janus_log_graph"));
+    assert!(generated.sparql_query.contains("?sensor ex:hasValue ?value ."));
+    assert!(generated.sparql_query.contains("GROUP BY ?sensor"));
+}
+
+#[test]
+fn baseline_source_window_must_exist() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:missing AS
+        SELECT ?sensor
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        REGISTER RStream ex:output AS
+        SELECT ?sensor
+        WHERE {
+          WINDOW ex:liveMinute { ?sensor ex:hasValue ?value . }
+        }
+    "#;
+
+    assert!(parser.parse(query).is_err());
+}
+
+#[test]
+fn baseline_source_window_must_be_historical_log() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:liveMinute AS
+        SELECT ?sensor
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        REGISTER RStream ex:output AS
+        SELECT ?sensor
+        WHERE {
+          WINDOW ex:liveMinute { ?sensor ex:hasValue ?value . }
+        }
+    "#;
+
+    assert!(parser.parse(query).is_err());
+}
+
+#[test]
+fn using_baseline_must_reference_defined_baseline() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        SELECT ?sensor
+        WHERE {
+          WINDOW ex:liveMinute { ?sensor ex:hasValue ?value . }
+        }
+    "#;
+
+    assert!(parser.parse(query).is_err());
+}
+
+#[test]
+fn old_using_baseline_aggregate_syntax_still_passes() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        REGISTER RStream ex:out AS
+        SELECT ?sensor ?reading
+        FROM NAMED WINDOW ex:hist ON LOG ex:store [START 1000 END 2000]
+        FROM NAMED WINDOW ex:live ON STREAM ex:stream [RANGE 500 STEP 100]
+        USING BASELINE ex:hist AGGREGATE
+        WHERE {
+            WINDOW ex:hist { ?sensor ex:mean ?mean }
+            WINDOW ex:live { ?sensor ex:reading ?reading }
+        }
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert_eq!(parsed.baseline.unwrap().mode, BaselineBootstrapMode::Aggregate);
+}
+
+#[test]
+fn main_select_can_compute_difference_between_live_avg_and_baseline_avg() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60000 STEP 1000]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400000 STEP 1000]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor
+               (AVG(?value) AS ?dayAvgValue)
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        SELECT ?sensor
+               (AVG(?value) AS ?minuteAvgValue)
+               ?dayAvgValue
+               ((AVG(?value) - ?dayAvgValue) AS ?difference)
+        WHERE {
+          WINDOW ex:liveMinute {
+            ?sensor ex:hasValue ?value .
+          }
+          GRAPH ex:dayBaseline {
+            ?sensor ex:dayAvgValue ?dayAvgValue .
+          }
+        }
+        GROUP BY ?sensor ?dayAvgValue
+        HAVING(AVG(?value) > ?dayAvgValue)
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert!(parsed.select_clause.contains("?difference"));
+    assert_eq!(parsed.ast.baseline_uses.len(), 1);
+    assert!(parsed.where_clause.contains("GROUP BY ?sensor ?dayAvgValue"));
+    assert!(parsed.where_clause.contains("HAVING(AVG(?value) > ?dayAvgValue)"));
+}
+
+#[test]
+fn query_defined_baseline_graph_template_is_extracted_structurally() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX ex: <http://example.org/>
+        FROM NAMED WINDOW ex:liveMinute ON STREAM ex:stream [RANGE 60 STEP 5]
+        FROM NAMED WINDOW ex:historyDay ON LOG ex:stream [OFFSET 0 RANGE 86400 STEP 5]
+        DEFINE BASELINE ex:dayBaseline ON WINDOW ex:historyDay AS
+        SELECT ?sensor (AVG(?value) AS ?dayAvgValue) (COUNT(?value) AS ?dayCount)
+        WHERE {
+          ?sensor ex:hasValue ?value .
+        }
+        GROUP BY ?sensor
+        REGISTER RStream ex:output AS
+        USING BASELINE ex:dayBaseline
+        SELECT ?sensor ?dayAvgValue ?dayCount
+        WHERE {
+          WINDOW ex:liveMinute {
+            ?sensor ex:hasValue ?value .
+          }
+          GRAPH ex:dayBaseline {
+            ?sensor ex:dayAvgValue ?dayAvgValue .
+            ?sensor ex:dayCount ?dayCount .
+          }
+        }
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert_eq!(parsed.baseline_graph_templates.len(), 1);
+    let template = &parsed.baseline_graph_templates[0];
+    assert_eq!(template.baseline_name, "http://example.org/dayBaseline");
+    assert_eq!(template.triples.len(), 2);
+    assert_eq!(
+        template.triples[0].predicate,
+        GraphTermTemplate::Iri("http://example.org/dayAvgValue".to_string())
+    );
+    assert_eq!(
+        template.triples[1].predicate,
+        GraphTermTemplate::Iri("http://example.org/dayCount".to_string())
+    );
+}
diff --git a/tests/live_stream_integration_test.rs b/tests/live_stream_integration_test.rs
index 1cf759d..c9b2c94 100644
--- a/tests/live_stream_integration_test.rs
+++ b/tests/live_stream_integration_test.rs
@@ -1,5 +1,8 @@
 use janus::core::RDFEvent;
+use janus::execution::ResultConverter;
+use janus::parsing::janusql_parser::JanusQLParser;
 use janus::stream::live_stream_processing::LiveStreamProcessing;
+use oxigraph::model::{GraphName, Literal, NamedNode, Quad};
 use std::thread;
 use std::time::Duration;
 
@@ -213,6 +216,95 @@ fn test_processing_state_management() {
     assert!(result.is_err());
 }
 
+#[test]
+fn test_live_query_joins_window_and_named_graph_with_group_by_having_and_arithmetic() {
+    let parser = JanusQLParser::new().unwrap();
+    let query = r#"
+        PREFIX : <http://example.org/>
+
+        FROM NAMED WINDOW :liveMinute ON STREAM :stream [RANGE 60000 STEP 1000]
+
+        REGISTER RStream :output AS
+        SELECT ?sensor
+               (AVG(?value) AS ?minuteAvgValue)
+               ?dayAvgValue
+               ((AVG(?value) - ?dayAvgValue) AS ?difference)
+        WHERE {
+            WINDOW :liveMinute {
+                ?sensor :hasValue ?value .
+            }
+            GRAPH :dayBaseline {
+                ?sensor :dayAvgValue ?dayAvgValue .
+            }
+        }
+        GROUP BY ?sensor ?dayAvgValue
+        HAVING(AVG(?value) > ?dayAvgValue)
+    "#;
+
+    let parsed = parser.parse(query).unwrap();
+    assert!(parsed.rspql_query.contains("GRAPH :dayBaseline"));
+    assert!(parsed.rspql_query.contains("GROUP BY ?sensor ?dayAvgValue"));
+    assert!(parsed.rspql_query.contains("HAVING(AVG(?value) > ?dayAvgValue)"));
+
+    let mut processor = LiveStreamProcessing::new(parsed.rspql_query.clone()).unwrap();
+    processor.register_stream("http://example.org/stream").unwrap();
+    processor.add_static_quad(Quad::new(
+        NamedNode::new("http://example.org/sensor1").unwrap(),
+        NamedNode::new("http://example.org/dayAvgValue").unwrap(),
+        Literal::new_typed_literal(
+            "11",
+            NamedNode::new("http://www.w3.org/2001/XMLSchema#decimal").unwrap(),
+        ),
+        GraphName::NamedNode(NamedNode::new("http://example.org/dayBaseline").unwrap()),
+    ));
+    processor.start_processing().unwrap();
+
+    for (timestamp, value) in [(1000, "20"), (1010, "22"), (1020, "24")] {
+        processor
+            .add_event(
+                "http://example.org/stream",
+                RDFEvent::new(
+                    timestamp,
+                    "http://example.org/sensor1",
+                    "http://example.org/hasValue",
+                    value,
+                    "",
+                ),
+            )
+            .unwrap();
+    }
+    processor.close_stream("http://example.org/stream", 5000).unwrap();
+
+    thread::sleep(Duration::from_millis(250));
+
+    let results = processor.collect_results(None).unwrap();
+    assert!(!results.is_empty(), "expected a live result from the graph join");
+
+    let converted = ResultConverter::new("live_graph_join".into())
+        .from_live_binding(results.into_iter().next().expect("expected at least one live binding"));
+    let binding = converted.bindings.first().expect("expected converted live binding");
+
+    let minute_avg_value = binding
+        .get("minuteAvgValue")
+        .expect("missing minuteAvgValue")
+        .parse::<f64>()
+        .expect("minuteAvgValue should be numeric");
+    let day_avg_value = binding
+        .get("dayAvgValue")
+        .expect("missing dayAvgValue")
+        .parse::<f64>()
+        .expect("dayAvgValue should be numeric");
+    let difference = binding
+        .get("difference")
+        .expect("missing difference")
+        .parse::<f64>()
+        .expect("difference should be numeric");
+
+    assert_eq!(minute_avg_value, 22.0);
+    assert_eq!(day_avg_value, 11.0);
+    assert_eq!(difference, 11.0);
+}
+
 #[test]
 fn test_unregistered_stream_error() {
     let query = r#"
diff --git a/vendor/rsp-rs/src/quad_container.rs b/vendor/rsp-rs/src/quad_container.rs
new file mode 100644
index 0000000..e69de29