block training-seen checkpoint evaluation
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@@ -12704,3 +12704,36 @@ Open:
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- Two adjacent positive AOIs and one real background AOI are not representative
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release evidence. Human review, broader independent geography and exact
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challenger provenance remain blocking.
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## 2026-08-09 - Training/evaluation membership gate
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### Corrected
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- Compared the non-overlap evaluation sample membership against the exact
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active and challenger training summaries. Turnhout and Westerlo are absent
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from both train splits; Postel-bos is present in both.
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- Reclassified the Postel detection counts as training-seen regression checks,
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not independent background validation. No existing metric or checkpoint was
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promoted on that evidence.
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- Extended the checkpoint evaluator with a strict multi-corpus membership gate.
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Governed runs now persist a blocked manifest and stop before PyTorch import,
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model loading and GPU inference if any evaluation AOI is training-seen.
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### Reproduced on Tower
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- Active training summary SHA-256:
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`49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a`.
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- Challenger training summary SHA-256:
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`7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c`.
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- Evaluation summary SHA-256:
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`c17a8c47eaecc2dfb38778ff5a612f9e6c4d67c9e90e31d3a6a66d8857adec4c`.
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- The strict run blocked on `postel_bos`, with
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`model_loading_attempted=false` and `gpu_inference_attempted=false`.
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- Blocked-manifest SHA-256:
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`62e8a9377ac87552936f472b0acf55d1d659ebf27f84ba8c4dbcefe7a374e1da`.
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### Remaining limitation
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- Independent real-background AOIs are still required. Literal 100% model
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correctness is not demonstrated; the system now refuses to misrepresent the
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known overlap as proof.
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+5
-1
@@ -1176,7 +1176,11 @@ This file now starts with the current implementation status. Older preparation/b
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no-data imagery.
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- [ ] Add multiple independent real-background AOIs and more geographically
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separated positive validation AOIs before interpreting non-overlap ranking
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as release evidence; Postel alone is not representative.
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as release evidence. Postel occurs in both compared train splits and is only
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a training-seen regression check, not independent validation.
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- [x] Add a fail-closed checkpoint gate that checks every evaluation AOI
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against the exact train split of every supplied model corpus before PyTorch
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import, model loading or GPU inference.
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- [ ] Convert the AI-assisted ledger into no stronger claim than experimental
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triage; a real human must independently review and sign the frozen artifacts
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before the governed training wrapper may unlock.
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@@ -216,3 +216,24 @@ and its threshold sensitivity, but still does not authorize promotion.
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Non-overlap is not overstated as statistical independence: the positive tiles
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remain adjacent and come from only two AOIs, edge objects can remain split, and
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there is only one real background AOI. The production model remains unchanged.
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## Training/evaluation membership correction
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The evaluation AOIs were subsequently checked against the exact tile summaries
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of both compared checkpoints. `turnhout` and `westerlo` do not occur in either
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train split. `postel_bos`, however, occurs in both: the active corpus contains
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20 training AOIs and the challenger corpus 26, with Postel included in each.
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The Postel image is real rather than blank/no-data, but it is training-seen.
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Consequently the positive Turnhout/Westerlo metrics remain a non-protected,
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adjacent-AOI candidate ranking; the Postel detection counts are only
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training-seen sanity/regression observations. They are not independent
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pure-background validation and cannot support release, threshold or
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generalisation claims. The earlier wording about a "real background AOI" must
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be read with this correction.
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The checkpoint evaluator now accepts exact training summaries and, in governed
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mode, fails before PyTorch import, model loading or GPU inference when any
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evaluation AOI overlaps any supplied train split. The reproduced gate blocked
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on `postel_bos` for both checkpoints. Its immutable machine-readable record is
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`artifacts/evidence/accuracy/model-training/20260809-v70-evaluation-independence-gate.json`.
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