{"id":"W4237473344","doi":"10.1515/iupac.88.1014","title":"Masculinization","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":[0.001044284,0.001210881,0.0009742536,0.004276399,0.0008467617,0.002278217,0.001474837,0.001014902,0.09675764],"category_scores_gemma":[0.008861077,0.0005147978,0.001420946,0.005638132,0.0004903107,0.001918762,0.002264957,0.001340785,0.05840198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008727953,"about_ca_system_score_gemma":0.001504524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01469052,"about_ca_topic_score_gemma":0.03108975,"domain_scores_codex":[0.998709,0.0002275633,0.0002776954,0.000356617,0.0002846411,0.0001445416],"domain_scores_gemma":[0.9964419,0.001236721,0.0006265162,0.0007726574,0.0007488256,0.0001734214],"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":[0.0001549673,0.00002213383,0.00775743,0.002637947,0.00007165632,0.00005766847,0.0001404159,0.0001671936,0.0001797203,0.00192212,0.9662555,0.02063319],"study_design_scores_gemma":[0.00005529654,0.00001678324,0.02239437,0.001078629,0.00003210247,0.0001625502,0.0001743036,0.00009478287,0.0001531434,0.001352586,0.974454,0.00003143613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000629934,0.0007731313,0.0001448676,0.0001743247,0.000109705,0.00003421574,0.9936202,0.0001509328,0.004362639],"genre_scores_gemma":[0.002599162,0.001022058,0.0007769403,0.0002977981,0.00005316118,0.0002671559,0.9917527,0.0001030479,0.003128024],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09675764,"threshold_uncertainty_score":0.3236866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119019172748162,"score_gpt":0.4531761258834062,"score_spread":0.4419859341559246,"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."}}