{"id":"W4249001298","doi":"10.1515/iupac.79.1519","title":"Ketosis","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; Compendium; Computer science; Toxicology; History; Chemistry; Philosophy; Biology; Linguistics; Archaeology","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":[0.00102554,0.001925643,0.001740381,0.003214239,0.0008639651,0.003109168,0.00238866,0.001916491,0.1339098],"category_scores_gemma":[0.008541047,0.0005833277,0.002186393,0.004496797,0.0003361301,0.001872717,0.001859866,0.001660323,0.1379379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354202,"about_ca_system_score_gemma":0.00282116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0116274,"about_ca_topic_score_gemma":0.02621637,"domain_scores_codex":[0.9985605,0.0002328168,0.0002906723,0.0004860029,0.0002790795,0.0001509466],"domain_scores_gemma":[0.9967985,0.000924622,0.000514275,0.0007779938,0.0007296081,0.0002550541],"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":[0.0003805673,0.00003015437,0.002120838,0.003110555,0.0001065221,0.00005311187,0.00002081516,0.0003181395,0.0001519009,0.0008194851,0.9822542,0.01063375],"study_design_scores_gemma":[0.0003669324,0.00003374024,0.004646117,0.00134395,0.0001235649,0.0001838065,0.00004909082,0.0002809088,0.0003096395,0.002165461,0.9904579,0.0000387972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001486704,0.0003300329,0.00009264776,0.00007950016,0.00004457506,0.00002198853,0.9973706,0.0002815339,0.001630537],"genre_scores_gemma":[0.0005763152,0.0003307023,0.0003370655,0.0001738527,0.0000173137,0.00009170064,0.9972265,0.00006377252,0.001182833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1339098,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322064857119102,"score_gpt":0.3859116101503581,"score_spread":0.3726909615791671,"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."}}