block checkpoint evaluation on ancestral exposure

artifacts/evidence/accuracy/model-training/20260809-v71-full-lineage-independence-gate.json

@@ -0,0 +1,76 @@
+{
+  "claim_boundary": "No checkpoint ranking or release claim is permitted.",
+  "dataset_yaml": "/app/storage/operator-data/yolo-building-aoi1024-bgaware512r8-nonoverlap-eval-r2/dataset.yaml",
+  "dataset_yaml_sha256": "c36f6d76aac4bc2f5e880e2f0133d176fb0dc277600e121570a944eee6db2c48",
+  "generated_at": "2026-08-09T20:08:28.285906+00:00",
+  "gpu_inference_attempted": false,
+  "model_lineage_independence_evidence": {
+    "evaluation_samples": [
+      "postel_bos",
+      "turnhout",
+      "westerlo"
+    ],
+    "evaluation_summary_path": "/app/storage/operator-data/yolo-building-aoi1024-bgaware512r8-nonoverlap-eval-r2/yolo_tile_dataset_summary.json",
+    "evaluation_summary_sha256": "c17a8c47eaecc2dfb38778ff5a612f9e6c4d67c9e90e31d3a6a66d8857adec4c",
+    "independent_for_all_supplied_lineage_corpora": false,
+    "interpretation": "At least one evaluation AOI was exposed in an ancestral train, validation, calibration or other split; the matrix is blocked before model loading.",
+    "lineage_corpora": [
+      {
+        "exposure_roles": {
+          "postel_bos": [
+            "train"
+          ],
+          "turnhout": [
+            "val"
+          ],
+          "westerlo": [
+            "val"
+          ]
+        },
+        "lineage_sample_count": 19,
+        "lineage_summary_path": "/app/storage/operator-data/yolo-building-aoi1024-expanded-minpx4vis035/yolo_tile_dataset_summary.json",
+        "lineage_summary_sha256": "1887e2ba5c719d33675a9ed85db99a274fd66d98d5f6ad44558d673620917201",
+        "overlapping_evaluation_samples": [
+          "postel_bos",
+          "turnhout",
+          "westerlo"
+        ]
+      },
+      {
+        "exposure_roles": {
+          "postel_bos": [
+            "train"
+          ]
+        },
+        "lineage_sample_count": 22,
+        "lineage_summary_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/yolo_tile_dataset_summary.json",
+        "lineage_summary_sha256": "49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a",
+        "overlapping_evaluation_samples": [
+          "postel_bos"
+        ]
+      },
+      {
+        "exposure_roles": {
+          "postel_bos": [
+            "train"
+          ]
+        },
+        "lineage_sample_count": 28,
+        "lineage_summary_path": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx3vis035/yolo_tile_dataset_summary.json",
+        "lineage_summary_sha256": "7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c",
+        "overlapping_evaluation_samples": [
+          "postel_bos"
+        ]
+      }
+    ],
+    "overlapping_evaluation_samples": [
+      "postel_bos",
+      "turnhout",
+      "westerlo"
+    ],
+    "status": "overlap"
+  },
+  "model_loading_attempted": false,
+  "schema_version": 3,
+  "status": "blocked_model_lineage_sample_exposure"
+}

artifacts/evidence/accuracy/model-training/20260809-v71-model-lineage-receipt.json

@@ -0,0 +1,115 @@
+{
+  "claim_boundary": "File/hash ancestry only; does not establish human review, protected-test validity or release fitness.",
+  "generated_at": "2026-08-09T20:10:17.734420+00:00",
+  "generic_base": {
+    "path": "/app/models/yolov8s.pt",
+    "sha256": "1f47a78bf100391c2a140b7ac73a1caae18c32779be7d310658112f7ac9aa78a",
+    "size_bytes": 22588772
+  },
+  "schema_version": 1,
+  "stages": [
+    {
+      "args": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-aoi1024expandedminpx4vis035e50/args.yaml",
+        "sha256": "ddb12aa459404a905c2d908210033f18346491823c1b059eec332c1a7f9a0263",
+        "size_bytes": 1839
+      },
+      "best_matches_model_copy": true,
+      "dataset_summary": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-expanded-minpx4vis035/yolo_tile_dataset_summary.json",
+        "sha256": "1887e2ba5c719d33675a9ed85db99a274fd66d98d5f6ad44558d673620917201",
+        "size_bytes": 135720
+      },
+      "dataset_yaml": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-expanded-minpx4vis035/dataset.yaml",
+        "sha256": "357730f4ee110efdb241d26c0479eeeea5200885cebeb8eae011e257beb058ba",
+        "size_bytes": 134
+      },
+      "model_copy": {
+        "path": "/app/models/geointel-building-yolov8s-aoi1024expandedminpx4vis035e50.pt",
+        "sha256": "a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196",
+        "size_bytes": 22499498
+      },
+      "name": "expanded",
+      "parent_model": {
+        "path": "/app/models/yolov8s.pt",
+        "sha256": "1f47a78bf100391c2a140b7ac73a1caae18c32779be7d310658112f7ac9aa78a",
+        "size_bytes": 22588772
+      },
+      "training_best": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-aoi1024expandedminpx4vis035e50/weights/best.pt",
+        "sha256": "a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196",
+        "size_bytes": 22499498
+      }
+    },
+    {
+      "args": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-smallbld-minpx3-img640-ft30/args.yaml",
+        "sha256": "2b482e6bbef26f433d4406e1acb5cbbf4ce63a63644b180a2d51b93f8c8f0dcb",
+        "size_bytes": 1882
+      },
+      "best_matches_model_copy": true,
+      "dataset_summary": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/yolo_tile_dataset_summary.json",
+        "sha256": "49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a",
+        "size_bytes": 158980
+      },
+      "dataset_yaml": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/dataset.yaml",
+        "sha256": "3a2ea97c35a18072a1ab6738cd673c0ecec5344b19461c91d72a15e138d46e8d",
+        "size_bytes": 134
+      },
+      "model_copy": {
+        "path": "/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt",
+        "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1",
+        "size_bytes": 22516074
+      },
+      "name": "active",
+      "parent_model": {
+        "path": "/app/models/geointel-building-yolov8s-aoi1024expandedminpx4vis035e50.pt",
+        "sha256": "a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196",
+        "size_bytes": 22499498
+      },
+      "training_best": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-smallbld-minpx3-img640-ft30/weights/best.pt",
+        "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1",
+        "size_bytes": 22516074
+      }
+    },
+    {
+      "args": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-reviewedexp6-minpx3-img640-ft20/args.yaml",
+        "sha256": "87e07dbed3ad12cc474e6b895147839431805b7044496277242e1538fcd91a0b",
+        "size_bytes": 1891
+      },
+      "best_matches_model_copy": true,
+      "dataset_summary": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx3vis035/yolo_tile_dataset_summary.json",
+        "sha256": "7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c",
+        "size_bytes": 204029
+      },
+      "dataset_yaml": {
+        "path": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx3vis035/dataset.yaml",
+        "sha256": "62e12f4433508cb0640f1d90ec0ffd389cd21ebe655fac4e7d9402f04da1168e",
+        "size_bytes": 138
+      },
+      "model_copy": {
+        "path": "/app/models/geointel-building-yolov8s-reviewedexp6-minpx3-img640-ft20.pt",
+        "sha256": "038f1f97a6afd534f29e1f392a730a58207b928ca01e31ab8d8fed6106705820",
+        "size_bytes": 22514794
+      },
+      "name": "challenger",
+      "parent_model": {
+        "path": "/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt",
+        "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1",
+        "size_bytes": 22516074
+      },
+      "training_best": {
+        "path": "/app/storage/training/operator-yolo/geointel-building-yolov8s-reviewedexp6-minpx3-img640-ft20/weights/best.pt",
+        "sha256": "038f1f97a6afd534f29e1f392a730a58207b928ca01e31ab8d8fed6106705820",
+        "size_bytes": 22514794
+      }
+    }
+  ],
+  "status": "complete_retained_lineage_to_generic_base"
+}

docs/CODEX_EXECUTION_LOG.md

@@ -12737,3 +12737,37 @@ Open:
 - Independent real-background AOIs are still required. Literal 100% model
   correctness is not demonstrated; the system now refuses to misrepresent the
   known overlap as proof.
+
+## 2026-08-09 - Full ancestral-corpus exposure correction
+
+### Corrected
+
+- Reconstructed the retained checkpoint ancestry from exact Ultralytics
+  `args.yaml` files and model hashes. The active model descends from the
+  expanded-min4 corpus; the challenger descends from the active model.
+- Found that the expanded ancestor used Postel-bos for training and
+  Turnhout/Westerlo for validation. All three v69 evaluation AOIs were therefore
+  exposed somewhere in the model family.
+- Replaced last-corpus/train-only checking with fail-closed inspection of every
+  split in every supplied ancestral corpus. Legacy CLI spellings remain safe
+  aliases to the full-lineage behavior.
+
+### Verified
+
+- The Tower gate blocked all three exposed AOIs with zero model-loading and
+  zero GPU-inference attempts.
+- Expanded ancestor summary SHA-256:
+  `1887e2ba5c719d33675a9ed85db99a274fd66d98d5f6ad44558d673620917201`.
+- Blocked-manifest SHA-256:
+  `f6effd94befd6df8d699bc66fbbea8a860b056cff9996be5f867f858807af65e`.
+- Model-lineage receipt SHA-256:
+  `84d8d7bd95acfb07b188b07ececfc5417fca80c087d7c04442dd2a4da5f43936`;
+  every retained training `best.pt` matches its named model copy byte-for-byte.
+- The production checkpoint and container image remain unchanged.
+
+### Accuracy boundary
+
+- The old Turnhout/Westerlo/Postel numbers are regression diagnostics only.
+  No independent positive or background accuracy evidence currently exists for
+  this model family; new AOIs must be provisioned without ancestry or spatial
+  exposure before another ranking is defensible.

docs/TODO.md

@@ -1179,8 +1179,9 @@ This file now starts with the current implementation status. Older preparation/b
   as release evidence. Postel occurs in both compared train splits and is only
   a training-seen regression check, not independent validation.
 - [x] Add a fail-closed checkpoint gate that checks every evaluation AOI
-  against the exact train split of every supplied model corpus before PyTorch
+  against every split of every supplied ancestral model corpus before PyTorch
-  import, model loading or GPU inference.
+  import, model loading or GPU inference. Turnhout/Westerlo were exposed as
+  validation in the base building model; Postel was exposed as training.
 - [ ] Convert the AI-assisted ledger into no stronger claim than experimental
   triage; a real human must independently review and sign the frozen artifacts
   before the governed training wrapper may unlock.

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

@@ -237,3 +237,29 @@ 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`.
+
+## Full model-lineage correction
+
+The preceding correction still considered only the final fine-tune corpus of
+each checkpoint. Exact retained Ultralytics arguments establish a longer
+ancestry: the active checkpoint was initialized from
+`geointel-building-yolov8s-aoi1024expandedminpx4vis035e50`, which was initialized
+from the generic `yolov8s.pt`; the challenger was then initialized from the
+active checkpoint. The copied model assets and retained `best.pt` files match
+byte-for-byte at each building-model stage.
+
+The ancestral expanded corpus exposes all three evaluation AOIs: `postel_bos`
+as train, and `turnhout` plus `westerlo` as validation. Therefore none of the
+v69 AOIs is independent of the complete model family. Turnhout/Westerlo can
+still be used as familiar regression diagnostics, but their metrics are not a
+fresh candidate-ranking result and must not support accuracy, uncertainty,
+generalisation or release claims.
+
+The gate now requires every ancestral corpus summary and checks every recorded
+split, including validation and calibration. A reproduced Tower run blocked on
+all three AOIs before PyTorch import, model loading or GPU inference. Evidence:
+`artifacts/evidence/accuracy/model-training/20260809-v71-full-lineage-independence-gate.json`.
+The byte-matching parent/output chain is retained separately in
+`artifacts/evidence/accuracy/model-training/20260809-v71-model-lineage-receipt.json`.
+Fresh geographically separated AOIs with complete spatial and lineage checks
+are required for the next meaningful evaluation.

scripts/README.md

@@ -5,13 +5,16 @@ weights on one declared, non-protected `val` split using CUDA. It records exact
 model and dataset hashes, standard Ultralytics detection metrics and a separate
 pure-background detection count. The output claim is validation ranking only;
 the script neither reads protected test data nor promotes a model.
-Governed comparisons must pass every candidate's exact tile-summary with
+Governed comparisons must pass the exact tile summary for every corpus in the
-`--training-summary` and enable `--require-training-sample-independence`. If
+complete ancestry of every candidate with `--lineage-summary` and enable
-any validation AOI occurs in any supplied train split, the script writes a
+`--require-lineage-sample-independence`. The check covers train, validation,
+calibration and every other recorded split, because an AOI used for ancestral
+checkpoint or threshold selection is also exposed. Any exposure writes a
 blocked manifest and exits before importing PyTorch, loading a model or using
-the GPU. A background detection count from a training-seen AOI is only a
+the GPU. The older `--training-summary` and
-regression check and must never be presented as independent background
+`--require-training-sample-independence` spellings remain aliases, but now use
-evidence.
+the same safer full-split semantics. A result from any lineage-exposed AOI is
+only a regression check and must never be presented as independent evidence.
 
 `render_operator_yolo_label_qa_contact_sheets.py` paginates complete visual
 reviews with `--tiles-per-sheet` (default `64`). This keeps large corpora

scripts/evaluate_yolo_checkpoint_matrix.py

@@ -111,8 +111,8 @@ def _sample_slugs(payload: dict[str, Any], *, split: str | None) -> set[str]:
     return samples
 
 
-def training_sample_independence_evidence(
+def model_lineage_independence_evidence(
-    dataset_yaml: Path, training_summaries: list[Path]
+    dataset_yaml: Path, lineage_summaries: list[Path]
 ) -> dict[str, Any]:
     evaluation_summary = dataset_yaml.parent / "yolo_tile_dataset_summary.json"
     if not evaluation_summary.is_file():
@@ -120,7 +120,7 @@ def training_sample_independence_evidence(
             "status": "unavailable",
             "reason": "evaluation dataset summary is unavailable",
             "evaluation_summary_path": str(evaluation_summary),
-            "independent_for_all_supplied_training_corpora": False,
+            "independent_for_all_supplied_lineage_corpora": False,
         }
 
     try:
@@ -134,18 +134,23 @@ def training_sample_independence_evidence(
             "reason": str(exc),
             "evaluation_summary_path": str(evaluation_summary),
             "evaluation_summary_sha256": sha256_file(evaluation_summary),
-            "independent_for_all_supplied_training_corpora": False,
+            "independent_for_all_supplied_lineage_corpora": False,
         }
 
     rows: list[dict[str, Any]] = []
     union_overlap: set[str] = set()
-    for raw_summary in training_summaries:
+    for raw_summary in lineage_summaries:
         summary = raw_summary.expanduser().resolve(strict=True)
         try:
             payload = json.loads(summary.read_text(encoding="utf-8"))
-            training_samples = _sample_slugs(payload, split="train")
+            all_samples = _sample_slugs(payload, split=None)
-            if not training_samples:
+            if not all_samples:
-                raise ValueError("training summary contains no training samples")
+                raise ValueError("lineage summary contains no samples")
+            roles_by_sample: dict[str, set[str]] = {}
+            for tile in payload["tiles"]:
+                sample_slug = str(tile["sample_slug"]).strip()
+                split = str(tile.get("split") or "unknown").strip()
+                roles_by_sample.setdefault(sample_slug, set()).add(split)
         except (json.JSONDecodeError, OSError, ValueError) as exc:
             return {
                 "status": "invalid",
@@ -153,32 +158,35 @@ def training_sample_independence_evidence(
                 "evaluation_summary_path": str(evaluation_summary),
                 "evaluation_summary_sha256": sha256_file(evaluation_summary),
                 "evaluation_samples": sorted(evaluation_samples),
-                "independent_for_all_supplied_training_corpora": False,
+                "independent_for_all_supplied_lineage_corpora": False,
             }
-        overlap = evaluation_samples & training_samples
+        overlap = evaluation_samples & all_samples
         union_overlap.update(overlap)
         rows.append(
             {
-                "training_summary_path": str(summary),
+                "lineage_summary_path": str(summary),
-                "training_summary_sha256": sha256_file(summary),
+                "lineage_summary_sha256": sha256_file(summary),
-                "training_sample_count": len(training_samples),
+                "lineage_sample_count": len(all_samples),
                 "overlapping_evaluation_samples": sorted(overlap),
+                "exposure_roles": {
+                    sample: sorted(roles_by_sample[sample]) for sample in sorted(overlap)
+                },
             }
         )
 
     if not rows:
         return {
             "status": "unavailable",
-            "reason": "no training summaries were supplied",
+            "reason": "no complete model-lineage summaries were supplied",
             "evaluation_summary_path": str(evaluation_summary),
             "evaluation_summary_sha256": sha256_file(evaluation_summary),
             "evaluation_samples": sorted(evaluation_samples),
-            "training_corpora": [],
+            "lineage_corpora": [],
             "overlapping_evaluation_samples": [],
-            "independent_for_all_supplied_training_corpora": False,
+            "independent_for_all_supplied_lineage_corpora": False,
             "interpretation": (
-                "Training/evaluation independence cannot be established "
+                "Model-lineage/evaluation independence cannot be established "
-                "without exact training summaries."
+                "without every ancestral corpus summary."
             ),
         }
 
@@ -188,29 +196,37 @@ def training_sample_independence_evidence(
         "evaluation_summary_path": str(evaluation_summary),
         "evaluation_summary_sha256": sha256_file(evaluation_summary),
         "evaluation_samples": sorted(evaluation_samples),
-        "training_corpora": rows,
+        "lineage_corpora": rows,
         "overlapping_evaluation_samples": sorted(union_overlap),
-        "independent_for_all_supplied_training_corpora": independent,
+        "independent_for_all_supplied_lineage_corpora": independent,
         "interpretation": (
-            "No evaluation AOI occurs in the train split of any supplied corpus."
+            "No evaluation AOI occurs in any split of any supplied ancestral corpus."
             if independent
-            else "At least one evaluation AOI occurs in a supplied train split; "
+            else "At least one evaluation AOI was exposed in an ancestral train, "
-            "the matrix is blocked before model loading."
+            "validation, calibration or other split; the matrix is blocked before "
+            "model loading."
         ),
     }
 
 
+def training_sample_independence_evidence(
+    dataset_yaml: Path, training_summaries: list[Path]
+) -> dict[str, Any]:
+    """Backward-compatible alias; evidence now checks every lineage split."""
+    return model_lineage_independence_evidence(dataset_yaml, training_summaries)
+
+
 def write_blocked_manifest(
     output: Path, dataset_yaml: Path, evidence: dict[str, Any]
 ) -> None:
     payload = {
-        "schema_version": 2,
+        "schema_version": 3,
         "generated_at": datetime.now(UTC).isoformat(),
-        "status": "blocked_training_sample_overlap",
+        "status": "blocked_model_lineage_sample_exposure",
         "claim_boundary": "No checkpoint ranking or release claim is permitted.",
         "dataset_yaml": str(dataset_yaml),
         "dataset_yaml_sha256": sha256_file(dataset_yaml),
-        "training_sample_independence_evidence": evidence,
+        "model_lineage_independence_evidence": evidence,
         "model_loading_attempted": False,
         "gpu_inference_attempted": False,
     }
@@ -261,8 +277,21 @@ def main() -> int:
     parser.add_argument("--output", type=Path, required=True)
     parser.add_argument("--background-prefix", action="append", required=True)
     parser.add_argument("--background-confidence", type=float, default=0.15)
-    parser.add_argument("--training-summary", type=Path, action="append", default=[])
+    parser.add_argument(
-    parser.add_argument("--require-training-sample-independence", action="store_true")
+        "--lineage-summary",
+        "--training-summary",
+        dest="lineage_summary",
+        type=Path,
+        action="append",
+        default=[],
+        help="tile summary for every corpus in the complete model ancestry",
+    )
+    parser.add_argument(
+        "--require-lineage-sample-independence",
+        "--require-training-sample-independence",
+        dest="require_lineage_sample_independence",
+        action="store_true",
+    )
     parser.add_argument("--device", default="cuda:0")
     parser.add_argument("--imgsz", type=int, default=640)
     parser.add_argument("--batch", type=int, default=8)
@@ -275,17 +304,19 @@ def main() -> int:
     dataset_yaml = args.dataset_yaml.expanduser().resolve(strict=True)
     images = validation_images(dataset_yaml)
     overlap_evidence = dataset_overlap_evidence(dataset_yaml)
-    independence_evidence = training_sample_independence_evidence(
+    independence_evidence = model_lineage_independence_evidence(
-        dataset_yaml, args.training_summary
+        dataset_yaml, args.lineage_summary
     )
-    if args.require_training_sample_independence and not args.training_summary:
+    if args.require_lineage_sample_independence and not args.lineage_summary:
         parser.error(
-            "--require-training-sample-independence requires at least one "
+            "--require-lineage-sample-independence requires every ancestral "
-            "--training-summary"
+            "--lineage-summary"
         )
     if (
-        args.require_training_sample_independence
+        args.require_lineage_sample_independence
-        and not independence_evidence["independent_for_all_supplied_training_corpora"]
+        and not independence_evidence[
+            "independent_for_all_supplied_lineage_corpora"
+        ]
     ):
         write_blocked_manifest(args.output, dataset_yaml, independence_evidence)
         return 3
@@ -374,14 +405,14 @@ def main() -> int:
         reverse=True,
     )
     payload = {
-        "schema_version": 2,
+        "schema_version": 3,
         "generated_at": datetime.now(UTC).isoformat(),
         "status": "ok" if successful else "failed",
         "claim_boundary": "Non-protected validation ranking only; no test, challenge or promotion claim.",
         "dataset_yaml": str(dataset_yaml),
         "dataset_yaml_sha256": sha256_file(dataset_yaml),
         "dataset_overlap_evidence": overlap_evidence,
-        "training_sample_independence_evidence": independence_evidence,
+        "model_lineage_independence_evidence": independence_evidence,
         "validation_image_count": len(images),
         "pure_background_prefixes": list(prefixes),
         "pure_background_confidence": args.background_confidence,

tests/test_evaluate_yolo_checkpoint_matrix.py

@@ -1,9 +1,11 @@
 import json
+import sys
 from pathlib import Path
 
 from scripts.evaluate_yolo_checkpoint_matrix import (
     dataset_overlap_evidence,
-    training_sample_independence_evidence,
+    main,
+    model_lineage_independence_evidence,
     write_blocked_manifest,
 )
 
@@ -67,7 +69,7 @@ def _write_summary(path: Path, rows: list[tuple[str, str]]) -> None:
     )
 
 
-def test_training_sample_independence_detects_overlap_for_each_corpus(
+def test_model_lineage_independence_detects_exposure_in_every_split(
     tmp_path: Path,
 ) -> None:
     evaluation = tmp_path / "evaluation"
@@ -80,24 +82,25 @@ def test_training_sample_independence_detects_overlap_for_each_corpus(
     )
     active = tmp_path / "active.json"
     challenger = tmp_path / "challenger.json"
-    _write_summary(active, [("postel_bos", "train"), ("mol", "train")])
+    _write_summary(active, [("postel_bos", "train"), ("turnhout", "val")])
     _write_summary(
         challenger, [("postel_bos", "train"), ("dessel", "train")]
     )
 
-    evidence = training_sample_independence_evidence(
+    evidence = model_lineage_independence_evidence(
         dataset_yaml, [active, challenger]
     )
 
     assert evidence["status"] == "overlap"
-    assert evidence["overlapping_evaluation_samples"] == ["postel_bos"]
+    assert evidence["overlapping_evaluation_samples"] == ["postel_bos", "turnhout"]
-    assert evidence["independent_for_all_supplied_training_corpora"] is False
+    assert evidence["independent_for_all_supplied_lineage_corpora"] is False
     assert [
-        row["overlapping_evaluation_samples"] for row in evidence["training_corpora"]
+        row["overlapping_evaluation_samples"] for row in evidence["lineage_corpora"]
-    ] == [["postel_bos"], ["postel_bos"]]
+    ] == [["postel_bos", "turnhout"], ["postel_bos"]]
+    assert evidence["lineage_corpora"][0]["exposure_roles"]["turnhout"] == ["val"]
 
 
-def test_training_sample_independence_accepts_disjoint_samples(tmp_path: Path) -> None:
+def test_model_lineage_independence_accepts_disjoint_samples(tmp_path: Path) -> None:
     evaluation = tmp_path / "evaluation"
     evaluation.mkdir()
     dataset_yaml = evaluation / "dataset.yaml"
@@ -108,14 +111,14 @@ def test_training_sample_independence_accepts_disjoint_samples(tmp_path: Path) -
     training = tmp_path / "training.json"
     _write_summary(training, [("mol", "train")])
 
-    evidence = training_sample_independence_evidence(dataset_yaml, [training])
+    evidence = model_lineage_independence_evidence(dataset_yaml, [training])
 
     assert evidence["status"] == "independent"
     assert evidence["overlapping_evaluation_samples"] == []
-    assert evidence["independent_for_all_supplied_training_corpora"] is True
+    assert evidence["independent_for_all_supplied_lineage_corpora"] is True
 
 
-def test_training_sample_independence_is_unavailable_without_training_corpus(
+def test_model_lineage_independence_is_unavailable_without_ancestral_corpus(
     tmp_path: Path,
 ) -> None:
     evaluation = tmp_path / "evaluation"
@@ -126,11 +129,11 @@ def test_training_sample_independence_is_unavailable_without_training_corpus(
         evaluation / "yolo_tile_dataset_summary.json", [("turnhout", "val")]
     )
 
-    evidence = training_sample_independence_evidence(dataset_yaml, [])
+    evidence = model_lineage_independence_evidence(dataset_yaml, [])
 
     assert evidence["status"] == "unavailable"
     assert evidence["overlapping_evaluation_samples"] == []
-    assert evidence["independent_for_all_supplied_training_corpora"] is False
+    assert evidence["independent_for_all_supplied_lineage_corpora"] is False
 
 
 def test_blocked_manifest_records_that_models_and_gpu_were_not_used(
@@ -145,11 +148,51 @@ def test_blocked_manifest_records_that_models_and_gpu_were_not_used(
         dataset_yaml,
         {
             "status": "overlap",
-            "independent_for_all_supplied_training_corpora": False,
+            "independent_for_all_supplied_lineage_corpora": False,
         },
     )
 
     payload = json.loads(output.read_text(encoding="utf-8"))
-    assert payload["status"] == "blocked_training_sample_overlap"
+    assert payload["status"] == "blocked_model_lineage_sample_exposure"
     assert payload["model_loading_attempted"] is False
     assert payload["gpu_inference_attempted"] is False
+
+
+def test_cli_blocks_lineage_validation_exposure_before_model_resolution(
+    tmp_path: Path, monkeypatch
+) -> None:
+    evaluation = tmp_path / "evaluation"
+    images = evaluation / "images" / "val"
+    images.mkdir(parents=True)
+    (images / "turnhout_r0_c0.png").write_bytes(b"not opened before gate")
+    dataset_yaml = evaluation / "dataset.yaml"
+    dataset_yaml.write_text("path: .\nval: images/val\n", encoding="utf-8")
+    _write_summary(
+        evaluation / "yolo_tile_dataset_summary.json", [("turnhout", "val")]
+    )
+    ancestor = tmp_path / "ancestor.json"
+    _write_summary(ancestor, [("turnhout", "val"), ("mol", "train")])
+    output = tmp_path / "blocked.json"
+    monkeypatch.setattr(
+        sys,
+        "argv",
+        [
+            "evaluate_yolo_checkpoint_matrix.py",
+            "--dataset-yaml",
+            str(dataset_yaml),
+            "--model",
+            str(tmp_path / "model-is-never-resolved.pt"),
+            "--output",
+            str(output),
+            "--background-prefix",
+            "background",
+            "--lineage-summary",
+            str(ancestor),
+            "--require-lineage-sample-independence",
+        ],
+    )
+
+    assert main() == 3
+    payload = json.loads(output.read_text(encoding="utf-8"))
+    assert payload["status"] == "blocked_model_lineage_sample_exposure"
+    assert payload["model_loading_attempted"] is False