The ROADMAP gates (macro-F1 >= 0.80, precision@coverage >= 0.90, ECE <= 0.05) were prose with no
tool behind them. scripts/calibration_report.py now computes them from prediction records and
refuses input it cannot honestly score:
- a split is re-derived from the pseudonymous subject key with the ingestion rule, so a corpus
cannot re-label its own splits; a contributor spanning two splits is refused before scoring
- the threshold is selected on validation only, and selecting on test or train is refused
- coverage, precision-at-coverage, macro-F1, per-class precision/recall, confusion, and expected
calibration error are computed on accepted suggestions, with classes that abstained away named
in excludedClasses instead of being scored as a silent zero
- exit codes carry the verdict: 0 GO, 3 BLOCKED, 2 refused
The release demo records the real harness against committed synthetic fixtures: a blocked
three-candidate comparison, a fixture engineered to clear every gate, and a leaked corpus refused.
Every number on the card is read back from the report the run wrote, and the captions state that
no model was measured, because a fixture is not evidence about accuracy.
The harness suite is wired into CI, check:syntax, and the release builder's own gates.