{"id":"W4230914648","doi":"10.1515/iupac.79.0786","title":"Agonist","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; CAS Registry Number; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001537279,0.001842839,0.00144313,0.003492605,0.001065263,0.003540008,0.002648855,0.001921459,0.1803808],"category_scores_gemma":[0.01279643,0.0005681799,0.001944655,0.005980364,0.0003597726,0.002351484,0.002160662,0.001855494,0.2407745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001749136,"about_ca_system_score_gemma":0.003074864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01921625,"about_ca_topic_score_gemma":0.03564163,"domain_scores_codex":[0.9974828,0.000426909,0.0003986827,0.0008997769,0.0005095598,0.0002822291],"domain_scores_gemma":[0.9951158,0.001157342,0.0004805953,0.001247176,0.001675466,0.0003236115],"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":[0.0001070751,0.00001942283,0.001401634,0.0007712382,0.00003918389,0.00001668288,0.00002025743,0.0001436963,0.00007554636,0.0006340854,0.9901787,0.006592515],"study_design_scores_gemma":[0.0001555431,0.00002001141,0.003396403,0.0005625844,0.0000441362,0.00006438539,0.00008489093,0.0002220691,0.0001837091,0.001530623,0.9937108,0.00002494654],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001121167,0.00009944692,0.0001007083,0.00009544291,0.00004150027,0.00002436731,0.9977335,0.000203738,0.001589227],"genre_scores_gemma":[0.0003819145,0.00009002617,0.0003366709,0.0001537404,0.00001414645,0.0001309038,0.9972187,0.00006337528,0.001610527],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8196192,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706727766796159,"score_gpt":0.4196593654242337,"score_spread":0.4025920877562721,"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."}}