{"id":"W4245783120","doi":"10.1515/iupac.88.1153","title":"Organogenesis","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":[0.001255148,0.001689847,0.001439451,0.004428939,0.0009939536,0.003236461,0.002311547,0.00142829,0.0930595],"category_scores_gemma":[0.006099591,0.0007551268,0.002447601,0.006093486,0.0005150769,0.001836249,0.00256061,0.002112151,0.0842054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577418,"about_ca_system_score_gemma":0.003037808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01610395,"about_ca_topic_score_gemma":0.028299,"domain_scores_codex":[0.9985056,0.0002209704,0.0003120518,0.0004411385,0.0003438937,0.0001763318],"domain_scores_gemma":[0.996685,0.0009398692,0.0004845043,0.0008997279,0.000788828,0.0002021493],"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":[0.0002682616,0.0000336428,0.004865953,0.005511837,0.0001280048,0.00009340981,0.00008609707,0.0005903263,0.0007215904,0.00214922,0.9657371,0.01981445],"study_design_scores_gemma":[0.000088236,0.0000177863,0.006418865,0.0009944122,0.00006314139,0.0001494765,0.00007028557,0.0001299181,0.0004113297,0.001476985,0.9901521,0.00002753767],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000234854,0.0005992936,0.0002423646,0.00007769639,0.00005598604,0.00002849249,0.9958032,0.0003350492,0.002623111],"genre_scores_gemma":[0.0008262194,0.0006809719,0.0007793544,0.0001440961,0.00001342429,0.0001478527,0.9956796,0.0001047344,0.001623911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0930595,"threshold_uncertainty_score":0.311315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165253534054491,"score_gpt":0.4482121731840968,"score_spread":0.436559637843552,"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."}}