{"id":"W4242082085","doi":"10.1515/iupac.79.1518","title":"Ketone Bodies","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; Chemical nomenclature; 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":[],"consensus_categories":[],"category_scores_codex":[0.001173582,0.001814068,0.001840622,0.004112092,0.0009404647,0.003213877,0.002753964,0.001926442,0.1187327],"category_scores_gemma":[0.009831118,0.0005963597,0.001735829,0.00710074,0.0004033637,0.002109913,0.002030548,0.001864447,0.1314314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508331,"about_ca_system_score_gemma":0.003347713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01378048,"about_ca_topic_score_gemma":0.02616924,"domain_scores_codex":[0.9981481,0.0002923222,0.0003482553,0.0005887543,0.0004219668,0.0002006104],"domain_scores_gemma":[0.9959469,0.001106852,0.0006227173,0.0009034478,0.00107034,0.0003497084],"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":[0.0002730826,0.00002730168,0.001697417,0.002495559,0.00006684152,0.00004151559,0.00002463642,0.0002434424,0.0001453935,0.001030702,0.9856837,0.008270404],"study_design_scores_gemma":[0.0002195338,0.00001886049,0.003296842,0.0009325445,0.00005949679,0.00008174967,0.0000465868,0.0001545466,0.000222938,0.001395973,0.9935448,0.00002618224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001093166,0.0002332138,0.00006734768,0.00005909619,0.0000306487,0.00001982172,0.9978691,0.000167618,0.001443781],"genre_scores_gemma":[0.0003875277,0.000240213,0.000288929,0.0001214475,0.00001258843,0.00009102426,0.9978145,0.00004193488,0.001001828],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1187327,"threshold_uncertainty_score":0.3972006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434539510069278,"score_gpt":0.3885208838984378,"score_spread":0.374175488797745,"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."}}