{"id":"W4235886360","doi":"10.1515/iupac.79.1795","title":"Phenome","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Hematological disorders and diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; CAS Registry Number; Computer science; Multidisciplinary approach; Toxicology; Medicine; Chemistry; Biology; Philosophy; Sociology; Linguistics; Social science","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":[],"consensus_categories":[],"category_scores_codex":[0.001009895,0.001954427,0.001573116,0.003033584,0.000840599,0.002485104,0.002776715,0.0017196,0.08474308],"category_scores_gemma":[0.008539582,0.0005878253,0.001912159,0.004987354,0.000343125,0.001640412,0.002023064,0.001717102,0.09373879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190246,"about_ca_system_score_gemma":0.002486394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01268626,"about_ca_topic_score_gemma":0.02987241,"domain_scores_codex":[0.9988639,0.0002000846,0.0001718353,0.0004551718,0.0001937157,0.0001152759],"domain_scores_gemma":[0.9977335,0.0007643049,0.0002622192,0.0005474664,0.0005184727,0.0001739655],"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":[0.0002642333,0.00003325161,0.003108562,0.002320985,0.0001361715,0.00006703175,0.00003781105,0.0005018495,0.0001912132,0.001023895,0.9834396,0.008875362],"study_design_scores_gemma":[0.0003136647,0.0000303333,0.005948282,0.00054903,0.0001158744,0.0001613649,0.00006517107,0.0004757895,0.0003256612,0.002357685,0.9896216,0.00003555682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001622025,0.000161223,0.0001319287,0.00008829727,0.00002666831,0.00001956997,0.9982435,0.0003361398,0.0008304834],"genre_scores_gemma":[0.000484291,0.0001567731,0.0004558059,0.0001197094,0.00001135134,0.0001201068,0.9978669,0.00007256257,0.0007125222],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08474308,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081420321343177,"score_gpt":0.4254664282322466,"score_spread":0.4046522250188149,"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."}}