{"id":"W7108230307","doi":"10.25504/fairsharing.a94677","title":"FAIRsharing record for: Hakai Data","year":2025,"lang":"","type":"dataset","venue":"FAIRsharing.org","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Margin (machine learning); Data collection; Information system; Historical record; Data system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001984204,0.001137176,0.001134524,0.005557899,0.001761673,0.005004478,0.002993277,0.00209597,0.368062],"category_scores_gemma":[0.01643073,0.0009559769,0.0009006904,0.01172961,0.0006049426,0.004133874,0.003283559,0.002236119,0.2709539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003696577,"about_ca_system_score_gemma":0.00578438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08695283,"about_ca_topic_score_gemma":0.09195835,"domain_scores_codex":[0.9981691,0.0001993719,0.0002428466,0.0004164357,0.0005771226,0.000395097],"domain_scores_gemma":[0.9917654,0.001758918,0.0007227722,0.002463328,0.00231547,0.0009740964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001603358,0.000003802451,0.0001792024,0.00008184423,0.000003429003,0.000003665105,0.000008729891,0.00003835087,0.00001009041,0.0003601208,0.9985471,0.0007477184],"study_design_scores_gemma":[0.00009418875,0.000004950401,0.002244113,0.0001877277,0.000006986765,0.00001423697,0.00007119333,0.0001308199,0.0000891933,0.001130294,0.9960031,0.00002318132],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003516075,0.00001428246,0.00002386008,0.00008740506,0.00002330854,0.000007802581,0.9978956,0.0002599676,0.001652456],"genre_scores_gemma":[0.000434663,0.00003629707,0.0001509969,0.00009316275,0.00001340673,0.00008042197,0.9963595,0.000257673,0.00257391],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.368062,"threshold_uncertainty_score":0.9013828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1406474824678136,"score_gpt":0.374359654357511,"score_spread":0.2337121718896974,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}