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    "browser": "Chromium 131.0.6778.205"
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  },
  "latency_target_met": true,
  "screening": {
    "candidates": 1391,
    "training_overlap_groups_excluded": 0,
    "calibration_overlap_groups_excluded": 0,
    "remaining_by_cohort": {
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      "heldout/general_human": 140,
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      "development/learner_human": 40,
      "heldout/learner_human": 86,
      "heldout/mage_ood": 144,
      "heldout/mage_paraphrased": 216,
      "heldout/apt_original": 96,
      "heldout/apt_polished": 288,
      "heldout/spans_mixed": 36,
      "heldout/spans_human": 36
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    "training_provenance": "Screened against RAID train_none, full MAGE train and the public GPTTrace training subset. Private teacher/student examples, attacked RAID training variants and DistilBERT training rows were unavailable. Independence from those unavailable rows is unverifiable."
  },
  "sources": {
    "MAGE": "https://huggingface.co/datasets/yaful/MAGE/tree/342663f0a2b775455c023f5d36a1341ff0ec5402",
    "APT-Eval": "https://github.com/ShoumikSaha/ai-polished-text/tree/53b1d2619a633e025998d6c7d0a12b0228b589da",
    "Heterogeneous AI Spans": "https://huggingface.co/datasets/open-text-detector/heterogeneous-ai-spans/tree/c8a59b129c34cfd9c67f739ae049abfff26fc2d3",
    "Ettin public training subset": "https://huggingface.co/datasets/nakas/gpttrace-text-train/tree/3f31325869bfc5414c1e8c713a6a4fd75b3eebb7",
    "Shijaku\u2013Canhasi TOEFL": "https://github.com/rexshijaku/chatgpt-generated-text-detection-corpus/tree/c0eb34cfd5c96cc02f7109a561eb753128cae9e6",
    "RAID train_none.csv": "sha256:c5467bca6fc7f5c728c676450c7f84ce401df6c6ccc6d82c47e3b5f3c6d6fce4"
  },
  "raid_official": {
    "ettin": {
      "with_attacks": {
        "auroc": 0.9989,
        "recall_at_fpr_1": 0.9891,
        "recall_at_fpr_5": 0.998
      },
      "without_attacks": {
        "auroc": 0.9995,
        "recall_at_fpr_1": 0.9953,
        "recall_at_fpr_5": 0.999
      },
      "source": "https://github.com/liamdugan/raid/pull/225",
      "source_note": "Official RAID CI, not a reproduction or a measurement of the browser pipeline."
    },
    "tmr": {
      "with_attacks": {
        "auroc": 0.9928,
        "recall_at_fpr_1": 0.9017,
        "recall_at_fpr_5": 0.9579
      },
      "without_attacks": {
        "auroc": 0.9985,
        "recall_at_fpr_1": 0.9856,
        "recall_at_fpr_5": 0.9965
      },
      "source": "https://huggingface.co/Oxidane/tmr-ai-text-detector#raid-leaderboard-official-results",
      "source_note": "Official leaderboard values as listed by the model author."
    },
    "distil": {
      "status": "unavailable"
    }
  },
  "limitations": [
    "Independent of Draftmark threshold selection. Training independence beyond the available corpora is unverified.",
    "MAGE and general metrics use stratified samples. APT-Eval uses matched pairs from selected polishing conditions.",
    "Heterogeneous AI Spans is a substitute for HACo-Det. Span metrics are experimental chunk projections.",
    "Offline corpus evaluations can include text below the browser's 150-word minimum or beyond its editor limits.",
    "DistilBERT failed browser/native score parity despite matching token IDs and was excluded from deployment.",
    "RAID test labels are hidden. Official published metrics are separate from our locally measured scores."
  ]
}