{"id":"W4234476949","doi":"10.1515/iupac.88.1163","title":"Ovary","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001260325,0.001319824,0.001452731,0.003697173,0.0009923801,0.003614428,0.002403538,0.001734599,0.2441538],"category_scores_gemma":[0.01301015,0.0006456468,0.001748794,0.006871834,0.0004069015,0.00302995,0.002640136,0.00159426,0.2363105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604633,"about_ca_system_score_gemma":0.00312292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01660082,"about_ca_topic_score_gemma":0.0253841,"domain_scores_codex":[0.9979401,0.0003133634,0.0004740354,0.0006009395,0.0004474594,0.0002240355],"domain_scores_gemma":[0.9944588,0.001399343,0.0007091489,0.001272122,0.00186315,0.0002974448],"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":[0.00009882401,0.00001050221,0.001025003,0.001429611,0.00002662622,0.000021055,0.00002721624,0.00007861323,0.0000820042,0.0009673323,0.9866217,0.009611486],"study_design_scores_gemma":[0.00009852977,0.00001115945,0.002946399,0.0008616471,0.00002303055,0.00006928655,0.00006282794,0.00006727096,0.0001103021,0.001247057,0.9944833,0.0000192115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001223089,0.0002504189,0.0001302309,0.0001931004,0.00007767521,0.00004016086,0.994762,0.0002754116,0.004148795],"genre_scores_gemma":[0.0005385056,0.0003218411,0.0004197771,0.0003363918,0.00002924019,0.000147007,0.9949562,0.00012058,0.003130457],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7558463,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02628989350039649,"score_gpt":0.4638627555504644,"score_spread":0.4375728620500678,"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."}}