{"id":"W4252996496","doi":"10.1515/iupac.76.0295","title":"Metabolic Enzymes","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Hazard; Relation (database); Computer science; Toxicology; Medicine; Pharmacology; Chemistry; Biology; Data mining; Philosophy; 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":[],"consensus_categories":[],"category_scores_codex":[0.0009667967,0.002738149,0.001986095,0.005052519,0.0008990759,0.003440294,0.002206978,0.001590594,0.0782444],"category_scores_gemma":[0.006276058,0.0008716207,0.002022669,0.009558748,0.0003811742,0.001929655,0.001916535,0.002075599,0.1098072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450098,"about_ca_system_score_gemma":0.002579481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055653,"about_ca_topic_score_gemma":0.01952069,"domain_scores_codex":[0.998565,0.0001995546,0.0002564056,0.0005440046,0.0003001037,0.000135001],"domain_scores_gemma":[0.9977779,0.0006927984,0.0003670761,0.0005562881,0.0004322826,0.0001736756],"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":[0.0003004917,0.00003992447,0.003231191,0.004674664,0.0001313175,0.00009207219,0.00007014116,0.0007433015,0.0008429997,0.001893681,0.9721065,0.01587373],"study_design_scores_gemma":[0.0001059913,0.0000187573,0.004200812,0.0006699569,0.00006590775,0.0001154681,0.00004530422,0.000206951,0.0004673159,0.001719052,0.9923534,0.00003123319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001560103,0.0004127838,0.0001793342,0.00004147295,0.0000238046,0.0000127369,0.9976379,0.0004262142,0.001109711],"genre_scores_gemma":[0.0003238592,0.0003289027,0.0005329264,0.00005996342,0.000005371768,0.00006318263,0.9980129,0.000092904,0.0005801014],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0782444,"threshold_uncertainty_score":0.2617536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009776068506866607,"score_gpt":0.3641733151829413,"score_spread":0.3543972466760747,"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."}}