{"id":"W4244261336","doi":"10.1515/iupac.79.1053","title":"Concentration–Response Relationship","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Multidisciplinary approach; Hazard; Computer science; Toxicology; Chemistry; Biology; Philosophy; Linguistics; Social science; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005434238,0.0003807237,0.0004194271,0.00007279068,0.0001084413,0.00003744016,0.0004008371,0.0004454933,0.00472897],"category_scores_gemma":[0.002099942,0.0002925326,0.0001878661,0.0001889223,0.0001041434,0.00009001869,0.0001680214,0.0006102784,0.00001956978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007246673,"about_ca_system_score_gemma":0.0002225748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002672831,"about_ca_topic_score_gemma":0.00003223308,"domain_scores_codex":[0.9976685,0.00008392762,0.0005398373,0.0004504547,0.0008372889,0.0004199907],"domain_scores_gemma":[0.998076,0.0006595523,0.0001816546,0.0006985856,0.0001826565,0.0002015406],"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":[0.0007062341,0.00009985003,0.00000633124,0.0001175535,0.00007859524,0.0000288097,0.000007674221,0.00005278731,0.0003346984,0.0001464876,0.9978204,0.000600513],"study_design_scores_gemma":[0.0009226894,0.00004195273,0.00004791988,0.0003156232,0.000103106,0.000003667988,0.000006876207,0.0001025446,0.0003076849,0.0002278815,0.9974988,0.0004213177],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001657774,0.0004089346,0.002213331,0.001626596,0.0004381017,0.0002453898,0.9946446,0.0001634924,0.00009375666],"genre_scores_gemma":[0.0005084721,0.0003565012,0.00005947372,0.0002066915,0.0007578576,0.00001985962,0.9963236,0.00003854973,0.001728988],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004709401,"threshold_uncertainty_score":0.9999527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453187401547094,"score_gpt":0.3610812068653039,"score_spread":0.346549332849833,"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."}}