{"id":"W4254731980","doi":"10.1515/iupac.87.0229","title":"Endocrine Disruptor","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Hormonal and reproductive studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Engineering ethics; Psychology; Chemistry; Engineering; Linguistics; Data mining; Organic chemistry; 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":[0.0009730615,0.00117789,0.001257055,0.003667125,0.0005707845,0.001936684,0.001464823,0.001075187,0.08221494],"category_scores_gemma":[0.008794538,0.0004751114,0.001421664,0.006417656,0.0002746392,0.001323172,0.001495533,0.001508174,0.04548999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001242134,"about_ca_system_score_gemma":0.002405158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01827918,"about_ca_topic_score_gemma":0.0321805,"domain_scores_codex":[0.9987399,0.000190726,0.0003360871,0.0003625909,0.0002588822,0.0001118302],"domain_scores_gemma":[0.9957984,0.001370191,0.00089697,0.0007128002,0.001017507,0.0002041849],"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":[0.0002935722,0.00002398251,0.007384824,0.006750935,0.0001773721,0.00008448271,0.00004694057,0.0004091591,0.000316289,0.001514475,0.9639677,0.01903025],"study_design_scores_gemma":[0.0001632792,0.00001973226,0.01123911,0.00137891,0.0001114281,0.0001919569,0.00004713859,0.0001188919,0.0002196066,0.001107419,0.9853786,0.00002399771],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000176186,0.0004137286,0.00008966832,0.00007714353,0.00002908221,0.00001623755,0.997343,0.00009642795,0.001758598],"genre_scores_gemma":[0.001421049,0.0008854255,0.000602315,0.0002850135,0.00002325056,0.0001128245,0.9946212,0.00005810981,0.00199088],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08221494,"threshold_uncertainty_score":0.2750363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776946203374808,"score_gpt":0.4313610253434869,"score_spread":0.4135915633097388,"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."}}