{"id":"W6908144350","doi":"10.25545/3kdbbw/u5pfer","title":"Minimum-Dataset.tab","year":2025,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001850231,0.004284445,0.002146606,0.005992525,0.001269167,0.004606276,0.003773873,0.003467799,0.3349021],"category_scores_gemma":[0.011142,0.001794827,0.002110195,0.007513769,0.0006875513,0.0038161,0.002903169,0.002612271,0.332294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001873326,"about_ca_system_score_gemma":0.002460226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008972318,"about_ca_topic_score_gemma":0.01498493,"domain_scores_codex":[0.9984534,0.0002291239,0.0001735238,0.0005789617,0.0003368994,0.0002280912],"domain_scores_gemma":[0.9966925,0.001257196,0.0002008466,0.0009702861,0.0005989589,0.0002802746],"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":[0.00008091858,0.00002442154,0.0001238863,0.0006930042,0.00002658878,0.000009047119,0.00001209566,0.0001746548,0.0001173623,0.000454045,0.9958541,0.002429803],"study_design_scores_gemma":[0.0007348708,0.00006004623,0.001172198,0.0002774654,0.00003673746,0.00006062525,0.00004518948,0.0007783457,0.0009368495,0.003185763,0.992664,0.000047976],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001133678,0.0001011655,0.0001795162,0.00009434685,0.00005699573,0.00002572065,0.9934121,0.00412007,0.00189669],"genre_scores_gemma":[0.0004753228,0.00008167453,0.0008754893,0.0001121664,0.00002011469,0.0001195912,0.9957605,0.001314686,0.001240438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.665098,"threshold_uncertainty_score":0.9486815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697028830480042,"score_gpt":0.2885867739287875,"score_spread":0.271616485623987,"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."}}