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    "kind": "analytical constant prediction on conserved test label counts"
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  "provenance": {
    "evaluationFirstCommit": "54311c5",
    "evaluationCommitDate": "2026-06-02",
    "sourceHead": "aa0e52bed41e080a649a86d31908de7544010d76",
    "sha256": {
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      "models/best_model.pt": "c31acef02088d9f3f206b8616b9473a4f5cb5f20ffb887e7113ec6ef0afeaafd",
      "models/driver_state_net.onnx": "bee797061b3aa3de2816b50c29d5a5c0ee9af3bcae61f6749e98624c633ddc55",
      "src/model.py": "26c92ce1aa0141f1342cd2187ab2ab7f24405334008e07c7d6354ce99f15478b",
      "src/features.py": "7c0fddc4783bbbcbbb95ec4d4b17a92a724a60ccc493726b4be92a539e43a06f",
      "scripts/train_model.py": "49290785a30861458318908dd56347a2027c985d05ae23e488e3b66cbfd31745",
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  "limitations": [
    "No per-window predictions, split manifests, participant counts or independent training seeds retained in this checkout.",
    "Overlapping windows share 75 of 90 frames; no independent-window confidence interval is reported.",
    "Per-domain macro-F1 follows sklearn default class union; class sets differ and are not directly comparable.",
    "AUC-V2 test supports only Distracted (274 windows); image ordering is not natural video time.",
    "Live demo applies external z-score; conserved evaluation feeds raw features to model LayerNorm.",
    "YOLO and manual overrides are absent from the conserved neural-network evaluation."
  ]
}