{"id":"W4231094520","doi":"10.1515/iupac.76.0254","title":"Incidence","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Hazard; Toxicology; Computer science; Environmental health; Medicine; Pharmacology; Chemistry; Biology; Linguistics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014453,0.00084269,0.001034823,0.0005303692,0.0001565318,0.0001148429,0.001445336,0.0006678284,0.01647587],"category_scores_gemma":[0.002867416,0.000633072,0.0002731786,0.0004903347,0.0004122735,0.0002553232,0.0005866328,0.0009080617,0.0004436626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762039,"about_ca_system_score_gemma":0.002431252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003052538,"about_ca_topic_score_gemma":0.00363412,"domain_scores_codex":[0.9939751,0.0002148498,0.0007756065,0.0010147,0.003108288,0.0009114248],"domain_scores_gemma":[0.9952345,0.0002118886,0.0006376734,0.002351093,0.001175188,0.0003896845],"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":[0.0002604378,0.0001900894,0.00001069646,0.0001100436,0.0001173819,0.000296973,0.000005755885,6.312487e-7,0.00004992421,0.000008143258,0.9975223,0.001427652],"study_design_scores_gemma":[0.001017919,0.0001823934,0.00003768248,0.0009843151,0.0001808253,0.00006031689,0.000007848361,0.000001622254,0.00003503058,0.0002619454,0.9963788,0.0008512578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005563699,0.0009696671,0.00006102027,0.0003088338,0.001095812,0.0004302661,0.9966753,0.0003186165,0.00008488492],"genre_scores_gemma":[0.000008385942,0.0005743306,0.0000704608,0.0003041705,0.001944896,0.00002800333,0.9961497,0.0002077267,0.0007122962],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0160322,"threshold_uncertainty_score":0.999612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01678615056746492,"score_gpt":0.4301397885366587,"score_spread":0.4133536379691938,"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."}}