{"id":"W4242273621","doi":"10.1515/iupac.88.1409","title":"Testis","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Testicular diseases and treatments","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); 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":[],"consensus_categories":[],"category_scores_codex":[0.0009734774,0.001231343,0.001459029,0.003423599,0.0007038598,0.002672359,0.002073661,0.001518107,0.1309455],"category_scores_gemma":[0.009441858,0.0005096943,0.001667854,0.005816923,0.000328376,0.001916151,0.001934034,0.001536614,0.1104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199794,"about_ca_system_score_gemma":0.002964727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01347435,"about_ca_topic_score_gemma":0.02658587,"domain_scores_codex":[0.9987697,0.0002050331,0.0002969218,0.0003503273,0.0002354544,0.0001425145],"domain_scores_gemma":[0.9966375,0.000895389,0.0005275057,0.0006869796,0.001021416,0.0002312972],"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":[0.0001625846,0.00001380931,0.002354954,0.003399752,0.00007367454,0.00005224566,0.0000342007,0.0001753593,0.0001505356,0.001246083,0.9781156,0.01422128],"study_design_scores_gemma":[0.0001457831,0.00001507306,0.004614404,0.001387364,0.00005965898,0.0001721984,0.00005232755,0.0001022157,0.0001603274,0.001377045,0.9918934,0.00002019297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001435802,0.0005336234,0.0001405752,0.0001491164,0.00006654741,0.00003447102,0.9959028,0.0002128713,0.002816375],"genre_scores_gemma":[0.0007000653,0.0006505803,0.0005324503,0.0003689861,0.00003316506,0.0001260551,0.9957678,0.00007253274,0.001748261],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1309455,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02084553049570222,"score_gpt":0.4566241262114014,"score_spread":0.4357785957156992,"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."}}