Copy bias model parameter arrays

[FlorianPfaff]

Summary

• copy learned bias-model parameter arrays during construction
• prevent caller-side NumPy mutations from silently changing a frozen model
• add a focused regression covering stored parameters and prediction stability

Bug

SensorBiasCorrectionModel is a frozen dataclass, but np.asarray(..., dtype=float) can return caller-owned floating-point arrays unchanged. The constructor therefore retained aliases for intercept, coefficients, feature_mean, and residual_std. Mutating those input arrays after construction changed the model and its predictions.

Fix

Take owned copies of the parameter arrays when normalizing their shapes. feature_scale already becomes an owned array through its sanitizing np.where operation.

Validation

• reproduced the pre-fix prediction change (3.0 to -105.0) after mutating constructor inputs
• verified the patched prediction remains 3.0
• PYTHONPATH=src python -m pytest -q tests/calibration/test_bias_parameter_ownership.py (1 passed)
• Python compilation check passed for the modified module and regression test
• branch comparison: two commits ahead, zero behind; only the calibration model and focused regression are changed

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	22.91s
✅ JSON	prettier	7	0	0	0	0.94s
✅ JSON	v8r	7		0	0	2.83s
✅ MARKDOWN	markdownlint	68	0	0	0	2.01s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	0.64s
✅ PYTHON	black	1490	183	0	0	94.65s
✅ PYTHON	isort	1490	329	0	0	2.63s
✅ REPOSITORY	betterleaks	yes		no	no	2.2s
✅ REPOSITORY	checkov	yes		no	no	52.63s
✅ REPOSITORY	gitleaks	yes		no	no	14.83s
✅ REPOSITORY	git_diff	yes		no	no	0.38s
✅ REPOSITORY	secretlint	yes		no	no	61.15s
✅ REPOSITORY	syft	yes		no	no	6.25s
✅ REPOSITORY	trivy-sbom	yes		no	no	5.57s
✅ REPOSITORY	trufflehog	yes		no	no	33.5s
✅ YAML	prettier	11	0	0	0	0.8s
✅ YAML	v8r	11		0	0	10.44s
✅ YAML	yamllint	11		0	0	0.61s

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