{"id":"W4255598616","doi":"10.1515/iupac.88.0783","title":"External Genitalia","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; 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":[0.0008115747,0.001118227,0.00115026,0.002843592,0.0005894138,0.001771046,0.001360224,0.0009960718,0.1818181],"category_scores_gemma":[0.007882724,0.000463109,0.001154504,0.004508442,0.0004136894,0.001545218,0.001812386,0.001203734,0.1226199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008415723,"about_ca_system_score_gemma":0.001761836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01147299,"about_ca_topic_score_gemma":0.0170348,"domain_scores_codex":[0.9990411,0.0001731153,0.0002289341,0.0002804245,0.0001806587,0.00009576069],"domain_scores_gemma":[0.9971105,0.001063168,0.0004887332,0.0005614629,0.0006581794,0.0001179394],"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":[0.0001580567,0.00001645535,0.002779739,0.002856164,0.00005271353,0.00008244962,0.00006647975,0.0001831344,0.0002120908,0.00117844,0.9638935,0.0285207],"study_design_scores_gemma":[0.00004920148,0.00001236079,0.007700346,0.001065434,0.00002505185,0.0002155336,0.00009096852,0.00005797175,0.0001229536,0.001189345,0.9894526,0.00001815855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003136587,0.0007288406,0.0002335762,0.0001541166,0.00008186826,0.00004783706,0.9925174,0.0002150898,0.005707611],"genre_scores_gemma":[0.002102781,0.001321397,0.001103963,0.0004914369,0.00004641922,0.0002808481,0.9889631,0.0001256808,0.005564437],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1818181,"threshold_uncertainty_score":0.6082422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258526020996824,"score_gpt":0.4553309979295803,"score_spread":0.4427457377196121,"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."}}