{"id":"W4241291510","doi":"10.1515/iupac.76.0357","title":"Receptor","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; Toxicokinetics; Relation (database); Hazard; Multidisciplinary approach; Computer science; Toxicology; Medicine; Pharmacology; Chemistry; Data mining; Biology; Political science; Linguistics; Philosophy; Law","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":[0.001367629,0.001955414,0.001444215,0.003998658,0.0009643915,0.003569966,0.002814178,0.001853489,0.1817129],"category_scores_gemma":[0.01035231,0.000692995,0.001754532,0.005580203,0.0004217795,0.002674,0.002225755,0.001809053,0.2431883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001650584,"about_ca_system_score_gemma":0.003012865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01633289,"about_ca_topic_score_gemma":0.02927572,"domain_scores_codex":[0.9976596,0.0003658663,0.0003365563,0.0008979465,0.0005064131,0.0002336327],"domain_scores_gemma":[0.9964253,0.001014037,0.0003887195,0.0009328889,0.0009860086,0.0002528835],"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":[0.00008660447,0.00001833017,0.0009311222,0.001070213,0.0000299781,0.00002592148,0.0000293726,0.000188613,0.0001579733,0.0008648059,0.9899282,0.006668894],"study_design_scores_gemma":[0.00007956559,0.00001453257,0.001802431,0.0004318856,0.0000265862,0.00005952588,0.00006268841,0.0001818368,0.0002193981,0.001198175,0.9959,0.00002340648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001086153,0.0001852478,0.0001443416,0.00009497169,0.00004120642,0.00002091109,0.9972332,0.0004285519,0.001742931],"genre_scores_gemma":[0.0003181145,0.0001409686,0.0003682824,0.0001374978,0.00001064427,0.000101606,0.9974233,0.0001001298,0.001399468],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1817129,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01288611953709485,"score_gpt":0.3843570145417695,"score_spread":0.3714708950046747,"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."}}