Gate completed checkpoints through training loop

docs/BELGIUM_BUILDING_TRAINING_LOOP.md

@@ -96,6 +96,11 @@ The checkpointed orchestrator invokes this builder after every rejected
 iteration, stores its checksum in `training-loop-state.json`, and uses the
 resulting dataset YAML for the next checkpoint. A restart resumes both the
 candidate weights and that exact failure-driven training input.
+An already completed out-of-band checkpoint enters the same contract with
+`--evaluate-initial-model`: the first iteration skips fitting, copies and
+hashes the checkpoint, and begins at calibration. A rejection then follows
+the identical failure-driven CUDA path and cannot open protected test evidence
+early.
 The orchestrator refuses to start unless every automated frozen-dataset gate
 passes and the corpus contains zero blank/low-variance positive tiles. The
 audit status may remain `needs_human_review` while training and objective

docs/CODEX_EXECUTION_LOG.md

@@ -11777,6 +11777,11 @@ Deployment evidence:
   leak-free failure-driven sampler automatically, records its evidence
   checksum and next dataset YAML in `training-loop-state.json`, and resumes
   both the candidate weights and exact sampling input after interruption.
+- Added `--evaluate-initial-model` for completed checkpoints such as v37. It
+  skips redundant fitting only for the first iteration, copies and hashes the
+  supplied weights, runs calibration first, and rejoins the same automatic
+  sampling/training path after rejection. Protected evidence remains closed
+  until calibration passes.
 - Confirmed v37 epoch 1 completed on CUDA with validation precision `0.601`,
   recall `0.455`, mAP50 `0.474` and mAP50-95 `0.205`; the run remains inactive
   and these internal-validation metrics are not release evidence.
@@ -11786,7 +11791,7 @@ Verified in this pass:
 - `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_belgium_training_iteration_assessment.py backend/tests/test_belgium_training_portfolio.py`
   (`12 passed`).
 - `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_failure_driven_yolo_sampling.py backend/tests/test_belgium_training_iteration_assessment.py`
-  (`15 passed`).
+  (`16 passed` after adding the completed-checkpoint entry contract).
 
 Open:
 

docs/TODO.md

@@ -973,6 +973,7 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Exclude GRB/PICC features created after the corresponding dated imagery period while retaining auditable rejection evidence.
 - [x] Allow the objective CUDA loop to consume an automatically clean `needs_human_review` corpus while keeping final human sign-off as a separate, mandatory promotion gate.
 - [x] Persist checksummed train-only failure-driven sampling after every rejected loop iteration and resume the next checkpoint from that exact dataset YAML.
+- [x] Add a guarded calibration-first entry point for completed checkpoints so v37 and future externally interrupted runs can rejoin the automated loop without redundant retraining.
 - [x] Evaluate the completed v36 YOLO11x checkpoint calibration-first on the rotated v30 holdouts; reject it before opening test/background because the regional calibration gate failed.
 - [ ] Finish and assess the leak-free v37 YOLO11x failure-driven CUDA iteration; open test/background evidence only if every calibration gate passes.