{"id":"W4241840949","doi":"10.1515/iupac.88.1472","title":"Vaginal Patency","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Maternal and Perinatal Health Interventions","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; Data mining; 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":[0.0003426884,0.000321182,0.0006565295,0.0001652759,0.0002199986,0.0000583306,0.0003279515,0.0002953937,0.02280914],"category_scores_gemma":[0.0002432294,0.0002541408,0.0002694504,0.00004835454,0.0001212156,0.00006112969,0.0001447373,0.0007613763,0.00002770184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001850015,"about_ca_system_score_gemma":0.0007879345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001309689,"about_ca_topic_score_gemma":0.0008393758,"domain_scores_codex":[0.9979237,0.00003459206,0.0004817385,0.0003700799,0.0008120292,0.0003778315],"domain_scores_gemma":[0.9978788,0.00001655083,0.0003061382,0.001003545,0.0004620587,0.0003329437],"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":[0.0003271873,0.000363648,0.00008369496,0.003946735,0.00007935858,0.001008201,0.000004475374,3.742275e-8,0.000001134656,0.000007464559,0.9889342,0.005243822],"study_design_scores_gemma":[0.001036102,0.0009238804,0.001515933,0.001995184,0.0001411263,0.000468313,0.000005420691,0.000003909453,0.000006455957,0.0001042869,0.9935753,0.0002240453],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005331079,0.001086764,0.00001738659,0.001722562,0.00138954,0.0003167116,0.9945079,0.00004914365,0.0003768947],"genre_scores_gemma":[0.0001860292,0.0008769952,0.0000504151,0.0003912747,0.001241394,0.00001940378,0.9820527,0.00002700702,0.01515481],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02278144,"threshold_uncertainty_score":0.9999911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090215831144639,"score_gpt":0.5017318456594254,"score_spread":0.460829687347979,"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."}}