{"id":"W4249752150","doi":"10.1515/iupac.88.0804","title":"Fetus","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","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":[0.0009891023,0.00112143,0.0009955112,0.002844027,0.0007479717,0.002427848,0.00174055,0.001334777,0.1400963],"category_scores_gemma":[0.007628877,0.000545528,0.001231805,0.004364955,0.0003001913,0.002009736,0.002215696,0.001366931,0.1413486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271001,"about_ca_system_score_gemma":0.002304222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01664293,"about_ca_topic_score_gemma":0.02748273,"domain_scores_codex":[0.9986451,0.0002160958,0.0002759978,0.0004200526,0.000296539,0.0001462208],"domain_scores_gemma":[0.9970053,0.000807245,0.0004038737,0.0006936849,0.0009063937,0.0001835365],"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":[0.0001243689,0.00001379385,0.001782737,0.001790881,0.00003819225,0.0000421829,0.00003975541,0.000136821,0.0001762006,0.001234137,0.9814165,0.01320436],"study_design_scores_gemma":[0.00006272673,0.000009917666,0.002957009,0.0006227029,0.00002115117,0.0000779571,0.00005276497,0.00007159772,0.0001579594,0.0009544488,0.9949979,0.00001381857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001460092,0.0002359781,0.0001359674,0.0001341425,0.00005803278,0.00002798401,0.9957346,0.0002218611,0.003305526],"genre_scores_gemma":[0.0005368043,0.0003262141,0.0004324871,0.000259503,0.00001846094,0.0001059858,0.9959032,0.00007774348,0.002339599],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1400963,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201639248573875,"score_gpt":0.461842195989233,"score_spread":0.4498258035034943,"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."}}