Handle stringified binary predict_proba labels

[FlorianPfaff]

Summary

• Detect stringified binary positive labels such as "1" and "true" when selecting the positive column from two-column predict_proba output.
• Keep the existing fallback behavior for nonnumeric/non-binary class labels.
• Add a regression test for reversed stringified binary class order (classes_ = ["1", "0"]).

Bug fixed

Before this change, CalibratedPairwiseAssociationModel respected classes_ = [1, 0] but defaulted to column 1 for classes_ = ["1", "0"], thereby returning the negative-class probability as the match probability.

Validation

• Locally syntax-checked the modified source file and new test file.
• Could not run the full repository test suite in the sandbox because direct GitHub cloning is unavailable there.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	49.46s
✅ JSON	prettier	7	0	0	0	0.91s
✅ JSON	v8r	7		0	0	7.58s
✅ MARKDOWN	markdownlint	68	0	0	0	1.77s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	0.43s
✅ PYTHON	black	872	1	0	0	39.3s
✅ PYTHON	isort	872	3	0	0	4.88s
✅ REPOSITORY	checkov	yes		no	no	43.44s
✅ REPOSITORY	gitleaks	yes		no	no	8.79s
✅ REPOSITORY	git_diff	yes		no	no	0.12s
✅ REPOSITORY	secretlint	yes		no	no	27.67s
✅ REPOSITORY	syft	yes		no	no	3.99s
✅ REPOSITORY	trivy-sbom	yes		no	no	8.86s
✅ REPOSITORY	trufflehog	yes		no	no	16.03s
✅ YAML	prettier	11	0	0	0	0.73s
✅ YAML	v8r	11		0	0	10.48s
✅ YAML	yamllint	11		0	0	0.44s

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