block training-seen checkpoint evaluation

docs/reviews/2026-08-09-ai-assisted-checkpoint-review.md

@@ -216,3 +216,24 @@ and its threshold sensitivity, but still does not authorize promotion.
 Non-overlap is not overstated as statistical independence: the positive tiles
 remain adjacent and come from only two AOIs, edge objects can remain split, and
 there is only one real background AOI. The production model remains unchanged.
+
+## Training/evaluation membership correction
+
+The evaluation AOIs were subsequently checked against the exact tile summaries
+of both compared checkpoints. `turnhout` and `westerlo` do not occur in either
+train split. `postel_bos`, however, occurs in both: the active corpus contains
+20 training AOIs and the challenger corpus 26, with Postel included in each.
+The Postel image is real rather than blank/no-data, but it is training-seen.
+
+Consequently the positive Turnhout/Westerlo metrics remain a non-protected,
+adjacent-AOI candidate ranking; the Postel detection counts are only
+training-seen sanity/regression observations. They are not independent
+pure-background validation and cannot support release, threshold or
+generalisation claims. The earlier wording about a "real background AOI" must
+be read with this correction.
+
+The checkpoint evaluator now accepts exact training summaries and, in governed
+mode, fails before PyTorch import, model loading or GPU inference when any
+evaluation AOI overlaps any supplied train split. The reproduced gate blocked
+on `postel_bos` for both checkpoints. Its immutable machine-readable record is
+`artifacts/evidence/accuracy/model-training/20260809-v70-evaluation-independence-gate.json`.