{"id":"W4254672138","doi":"10.1515/iupac.88.1083","title":"Multigenerational Study","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":[0.00338591,0.0009177261,0.001520097,0.004036455,0.001374392,0.002092786,0.002431487,0.001734774,0.08392376],"category_scores_gemma":[0.02481963,0.0005720979,0.002544482,0.007542763,0.0004465733,0.001679897,0.003076915,0.001995283,0.02401745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530663,"about_ca_system_score_gemma":0.002695371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02157491,"about_ca_topic_score_gemma":0.04304213,"domain_scores_codex":[0.9961482,0.00095792,0.0008591933,0.001112345,0.0005633155,0.000359054],"domain_scores_gemma":[0.9880757,0.003655439,0.002012475,0.003034837,0.002703306,0.0005181497],"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":[0.0005883579,0.00006509644,0.04266151,0.005342448,0.001035209,0.0003071121,0.0003535946,0.000312111,0.0001341895,0.003610087,0.9239691,0.02162133],"study_design_scores_gemma":[0.00034429,0.00006819769,0.07524136,0.00486929,0.0007292465,0.0008144621,0.0005346107,0.000254381,0.0002481456,0.005446779,0.9113632,0.00008610231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002074006,0.001718982,0.0007600974,0.0004166852,0.0001846102,0.0002287507,0.9892565,0.000123507,0.005236947],"genre_scores_gemma":[0.01318444,0.00192158,0.002161949,0.001141681,0.0001446421,0.00251546,0.9707032,0.0001756509,0.008051472],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08392376,"threshold_uncertainty_score":0.280753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01651219472980763,"score_gpt":0.4811805813098464,"score_spread":0.4646683865800387,"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."}}