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feat: Phase F F7 negative result calibration link -- NCL- schema closes NRR-to-CAL learning loop, coverage consistency enforced, 63 tests - #901
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…es NRR-to-CAL learning loop, coverage consistency enforced, 63 tests (#901)
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Implements F7 from NEXT_100_PR_MAP: calibration link from negative-result entries to intake reports.
What
negative_result_calibration_link.py: NCL- prefixed dataclass linking NRR- records to CAL- intakeNegativeResultCalibrationLink: 10 fieldsVALID_LINK_TYPES: 5 values (batch_failure_feedback, single_candidate_rejection, systematic_failure_pattern, assay_protocol_failure, data_quality_rejection)VALID_LINK_STATUSES: 5 values (pending, submitted, accepted, rejected, superseded)validate_negative_result_calibration_link(): 14 rules including bidirectional coverage consistencyWhy
Negative results are only useful if they reach the calibration pipeline. The NCL- schema makes the NRR→CAL feedback loop an auditable artifact.
Disconfirming pass