{"id":"W4255586667","doi":"10.1515/iupac.81.0900","title":"Teratogenesis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Relation (database); Computer science; Ecology; Risk assessment; Biology; Data mining; Philosophy; Linguistics","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":[0.00152372,0.001727335,0.001634673,0.003579112,0.001046969,0.002912365,0.002769551,0.002108438,0.07143653],"category_scores_gemma":[0.008509243,0.0006988755,0.001863023,0.003802682,0.0004527732,0.001446882,0.002196078,0.002581341,0.09650608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001714026,"about_ca_system_score_gemma":0.002836883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01284494,"about_ca_topic_score_gemma":0.02695357,"domain_scores_codex":[0.9985877,0.0002350138,0.0002135179,0.0004284054,0.0003402719,0.0001950666],"domain_scores_gemma":[0.9954361,0.001341949,0.0006854187,0.001236767,0.0009415727,0.0003581275],"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":[0.0002510844,0.00004541088,0.005753688,0.002192033,0.0000912239,0.00009824395,0.00003578929,0.0004956138,0.0004107094,0.001159701,0.9764876,0.01297888],"study_design_scores_gemma":[0.0002224642,0.00003459938,0.008442478,0.000860849,0.00008614279,0.000383321,0.00005980548,0.0003487889,0.0007070999,0.002022746,0.9867952,0.00003660985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003115156,0.0004577294,0.0001890858,0.0001163323,0.00004996317,0.0000235794,0.9971536,0.0003321003,0.001366015],"genre_scores_gemma":[0.0007884458,0.0003343478,0.0005456357,0.0001466788,0.00001088751,0.0000964037,0.9968041,0.00006380798,0.001209678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07143653,"threshold_uncertainty_score":0.238979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324309040518289,"score_gpt":0.3839521919483544,"score_spread":0.3707091015431715,"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."}}