evidence/claim4/method.md

Claim 4 released-artifact audit method

The fixed campaign entrypoint first reruns the accepted Claims 1–3 regression suite. It then:

1. retrieves the public author model listing and each released target-specific checkpoint manifest with an explicit browser user agent;
2. pins the observed model revisions and checks for split, seed, trainer, or training-row manifests;
3. recomputes Kendall tau-b for the retained 512-row ENAS and NASNet unified base-checkpoint predictions;
4. recomputes each Kendall result with an independent O(n²) pair-count implementation;
5. recomputes the paper's five-space arithmetic and all named comparator inequalities; and
6. permutes targets 200 times with seed 20260926476 and confirms that the negative control cannot exceed the GNN acceptance threshold.

The retained unified checkpoint rows repair the previous judge's metric criticism but do not substitute for the unavailable target-specific ENAS and NASNet checkpoints. The audit therefore passes as an audit while the claim verdict remains BLOCKED.

Exact command:

uv run --locked python repro/src/run_campaign.py

Pinned environment: Python 3.12, transformers==4.53.2, torch==2.7.1 from the CPU-only PyTorch index, and all complete resolutions in uv.lock.