{"id":"W4255043100","doi":"10.1515/iupac.88.0535","title":"Birth","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":[0.001184137,0.001050281,0.001017996,0.003051542,0.0008334844,0.003041993,0.001923449,0.001414169,0.1858715],"category_scores_gemma":[0.01113407,0.0005206192,0.001350646,0.005219881,0.0002958843,0.002369509,0.002237375,0.001595623,0.1891776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155548,"about_ca_system_score_gemma":0.002388567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01891914,"about_ca_topic_score_gemma":0.02972336,"domain_scores_codex":[0.9983805,0.0002755818,0.0003366219,0.0005116572,0.0003219343,0.000173669],"domain_scores_gemma":[0.9961979,0.0009734476,0.0004334141,0.0009085019,0.001238952,0.0002477105],"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":[0.00009197897,0.00001297979,0.001776715,0.001121782,0.00003410197,0.00002243054,0.00003004436,0.0001055438,0.00006878816,0.001118806,0.9848707,0.01074603],"study_design_scores_gemma":[0.00007014235,0.00001160452,0.003927308,0.0006467398,0.00002048916,0.00005595858,0.00007105395,0.00008244187,0.0001097006,0.001173149,0.9938142,0.00001716855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001421527,0.0001853131,0.0001236336,0.0001369798,0.00006595781,0.00002700151,0.99564,0.0002424998,0.003436393],"genre_scores_gemma":[0.0005352022,0.0002446911,0.000342714,0.0001984347,0.00001926861,0.00009913889,0.995594,0.00008128434,0.002885205],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1858715,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163659275565125,"score_gpt":0.4524366265063761,"score_spread":0.4408000337507248,"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."}}