{"id":"W4251853229","doi":"10.1515/iupac.88.1462","title":"Urogenital","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Medical and Health Sciences Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Reproductive system; Computer science; Biology; Linguistics; Philosophy; Data mining","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":[0.0007506394,0.001030162,0.001499237,0.004037602,0.0006348889,0.002278521,0.001397187,0.001171122,0.1534185],"category_scores_gemma":[0.01124802,0.0004377947,0.001587435,0.007686527,0.0003151006,0.00173378,0.001782626,0.001563816,0.07412845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114551,"about_ca_system_score_gemma":0.002758432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01597683,"about_ca_topic_score_gemma":0.0220838,"domain_scores_codex":[0.9987292,0.0001969603,0.0003437233,0.0003513039,0.0002345665,0.0001443386],"domain_scores_gemma":[0.9959453,0.001321441,0.0006995927,0.0007025955,0.001101815,0.0002292919],"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":[0.0002335023,0.00001902929,0.003718519,0.00589953,0.0001076948,0.00008384723,0.0000373091,0.0002058496,0.000130953,0.001262325,0.9617848,0.02651664],"study_design_scores_gemma":[0.0001730362,0.00002483322,0.01184629,0.003721926,0.00008767601,0.0003479983,0.0000924559,0.0001110548,0.0001491315,0.001703984,0.9817115,0.00003011501],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002677924,0.001100976,0.0001161082,0.0001699756,0.00008972712,0.0000374915,0.9940047,0.0001446713,0.004068648],"genre_scores_gemma":[0.00156112,0.001693858,0.0005137405,0.0004111558,0.00005887993,0.0001705932,0.9923629,0.00007426579,0.003153477],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1534185,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05717712016054542,"score_gpt":0.5602485312091775,"score_spread":0.5030714110486321,"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."}}