{"id":"W4235063404","doi":"10.1515/iupac.88.1471","title":"Vaginal Cornification","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Female Genital Mutilation/Cutting Issues","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); Human reproduction; Computer science; Biology; Linguistics; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008464391,0.001231364,0.001168348,0.004716871,0.0006085551,0.002228131,0.001453712,0.00130695,0.09765252],"category_scores_gemma":[0.009365437,0.0005013081,0.001900413,0.005994704,0.0004134612,0.001729137,0.001806337,0.001560304,0.05138322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009965897,"about_ca_system_score_gemma":0.002149967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01433302,"about_ca_topic_score_gemma":0.02456006,"domain_scores_codex":[0.9989775,0.0001643157,0.000315862,0.0002468654,0.000191411,0.0001040583],"domain_scores_gemma":[0.9958937,0.001401304,0.001048157,0.0006267711,0.0008415134,0.0001884938],"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":[0.0003537547,0.00002842903,0.00684993,0.008674777,0.00011307,0.0001404777,0.00009418016,0.0002994127,0.0002625844,0.00167932,0.9498087,0.03169528],"study_design_scores_gemma":[0.0001426197,0.00002660468,0.01583702,0.004692245,0.00008363782,0.0003650228,0.0001657293,0.000157594,0.0002620785,0.001730743,0.9764947,0.00004203838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004704136,0.001163623,0.0002030416,0.0001465618,0.0001062094,0.00007261542,0.993852,0.0001771565,0.003808316],"genre_scores_gemma":[0.002503049,0.002221546,0.001334877,0.0003677541,0.00005957326,0.0003865379,0.9891117,0.0001124492,0.003902434],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09765252,"threshold_uncertainty_score":0.3266802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03202423406711095,"score_gpt":0.467575893602703,"score_spread":0.435551659535592,"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."}}