SkillScreen-2B-Package / evaluation.json
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Release v0.1.0: full-data deployment model, inference entry point and OOF thresholds
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{
"mode": "package32k",
"seed": 42,
"records": 11831,
"malicious": 6436,
"benign": 5395,
"auprc_average_precision": 0.9990312216598736,
"auroc": 0.9984704751021387,
"folds_sha256": "c11c6f68dd23fddb70d7090512d93f5be54bb216596175d44fcaa7e7df80e202",
"oof_sha256": "f46a75a97b3716c787bd7116fb837ee0124be34055c1dbce75e6f6d1c27933f9",
"folds": [
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}
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"created_at": "2026-11-10T07:34:36.103352+00:00",
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"balanced": {
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"selection": "Balanced maximizes recall minus FPR among predeclared 95/98/99% OOF recall gates; ties prefer higher recall. High-recall targets 99% OOF recall.",
"scope": "Pooled three-fold out-of-fold scores. Every score is from a model that excluded that skill group. Thresholds transfer to a separate full-data refit; these are not held-out test results of that refit."
}