{"id":"W4240115194","doi":"10.1515/iupac.79.1051","title":"Concentration–Effect 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; Computer science; Hazard; 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":[0.0003796509,0.0004104546,0.0004944794,0.00005889384,0.0001026426,0.00003610117,0.0003749533,0.0004545262,0.003787319],"category_scores_gemma":[0.00121873,0.0002941187,0.0002124788,0.0001761426,0.00008914367,0.00008541976,0.0001567403,0.0006552988,0.00001827684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006065526,"about_ca_system_score_gemma":0.0001117025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003825967,"about_ca_topic_score_gemma":0.00004065542,"domain_scores_codex":[0.9977601,0.00005691483,0.0004907147,0.0004560362,0.0008187294,0.0004175302],"domain_scores_gemma":[0.9983673,0.0004973283,0.0001697992,0.0006508694,0.000131527,0.0001831467],"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":[0.000107707,0.00006354588,0.0000182128,0.0002689938,0.00009434755,0.00002014166,0.000003602679,0.0000404518,0.000131152,0.0001591324,0.9976193,0.001473408],"study_design_scores_gemma":[0.0009896611,0.00006579908,0.00002041219,0.000401137,0.0001586427,0.000002921224,0.000001938335,0.0001114574,0.0004725264,0.0001715371,0.9971967,0.0004073144],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000752441,0.0005053238,0.001686776,0.0006361827,0.0005198295,0.0003242822,0.9958234,0.0001700194,0.0002589172],"genre_scores_gemma":[0.0004270149,0.0003994906,0.00003158764,0.0001255192,0.001072916,0.00002629636,0.9968957,0.00003803776,0.0009834773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.003769043,"threshold_uncertainty_score":0.9999511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113588497422882,"score_gpt":0.3566173477161964,"score_spread":0.3454814627419676,"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."}}