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Marius CiepluchandClaude Opus 5
d9d6dfdbcf
Design approved in session. Every one of the 36 criteria is claimed by a task. Group 1 calls no model at all. The candidate enumerator, the ceiling report and the stop-or-go reading are offline, so the condition that ends this feature -- a deciding slice whose ceiling sits below its recorded detection rate -- is reachable before a cent is spent. The ruleset variant of this same design would have failed that condition at 12.1% against 64.9%. Group 2 is the only work that touches scoring.py, and its observable is that nothing changes: the recorded round-zero artifacts are the pin, and if they cannot be reproduced exactly then the refactor is wrong, not the numbers. Group 3 builds the detector, and task 3.3 is the test that would have caught the defect this spec exists for -- two runs must make an identical sequence of model calls. It lives in the suite and runs repeatedly, not in a one-off measurement. Group 4 is the maintainer's emphasis as code: deciding slices, development slices, the cross-slice rejection by name, and the overfitting gap printed beside every headline number. Group 5 compares the two detectors per slice, re-measures the trajectory count and the noise floor, and names -- without amending -- the learning-harness requirements that a collapsed floor would retire. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG