{"id":"W4254809073","doi":"10.1515/iupac.79.0774","title":"Adrenergic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics","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":[0.0007396617,0.001542199,0.001561135,0.002311531,0.0005935735,0.0020082,0.001777383,0.00151779,0.08704846],"category_scores_gemma":[0.006573224,0.0004269182,0.001604622,0.003678848,0.0002154462,0.001188422,0.001245999,0.001473222,0.08239938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008922198,"about_ca_system_score_gemma":0.001592059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01171504,"about_ca_topic_score_gemma":0.0250402,"domain_scores_codex":[0.999036,0.0001359921,0.0001876013,0.0003462761,0.0001757437,0.0001184468],"domain_scores_gemma":[0.9977891,0.0006534819,0.0003832273,0.0004599522,0.0005439989,0.0001701279],"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":[0.0005293802,0.00004187125,0.005196476,0.00294107,0.0001550634,0.00006786103,0.00002696747,0.0002433574,0.0002612408,0.0005012832,0.9764966,0.01353874],"study_design_scores_gemma":[0.0005068628,0.00005825919,0.02142704,0.001746059,0.0002394819,0.000352453,0.00009030213,0.0002922716,0.0004156043,0.00166182,0.9731508,0.00005906736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000263232,0.0003887478,0.00006558178,0.00007330633,0.00004308134,0.0000172469,0.9978042,0.000101614,0.001243037],"genre_scores_gemma":[0.0009441489,0.0003375171,0.0002621269,0.0001834808,0.00002724471,0.0001158348,0.9968137,0.00003074816,0.001285154],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9129515,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005302612187823427,"score_gpt":0.3176334132047971,"score_spread":0.3123308010169737,"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."}}