{"id":"W4242074791","doi":"10.1515/iupac.76.0179","title":"Concentration–Response Relationship","year":2016,"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":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Hazard; Multidisciplinary approach; Toxicology; Computer science; Medicine; Chemistry; Pharmacology; Data mining; Biology; Political science; Linguistics; Law; 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":[0.001519829,0.00208785,0.001875354,0.004580947,0.0005823072,0.002657397,0.002690255,0.001846118,0.1127639],"category_scores_gemma":[0.0149164,0.0007359458,0.002741469,0.006797641,0.0003215116,0.001850304,0.00173535,0.001846288,0.08357168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595266,"about_ca_system_score_gemma":0.002381129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209688,"about_ca_topic_score_gemma":0.02221151,"domain_scores_codex":[0.9974076,0.0003716514,0.0005123519,0.001002901,0.0005449699,0.0001606255],"domain_scores_gemma":[0.9937472,0.003016014,0.0008165851,0.001143984,0.001073678,0.0002025841],"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":[0.0002116325,0.00006466823,0.004813168,0.004515589,0.0002229868,0.00005094986,0.00003962435,0.0007709335,0.0003429465,0.001178772,0.9737487,0.01403999],"study_design_scores_gemma":[0.0002213211,0.00004223132,0.00936968,0.0009722862,0.0001534269,0.0001285708,0.00004931652,0.0005416416,0.0004205742,0.002355915,0.9856984,0.0000465856],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001380808,0.0002618017,0.0001581305,0.00005020024,0.00002914945,0.00002181341,0.9983464,0.0002197155,0.0007746249],"genre_scores_gemma":[0.0008254859,0.0003107855,0.0007014328,0.0001257009,0.0000158266,0.0002104202,0.9966174,0.00007276929,0.001120167],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1127639,"threshold_uncertainty_score":0.3772328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299817309024344,"score_gpt":0.4304983690448655,"score_spread":0.4175001959546221,"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."}}