{"id":"W4241390712","doi":"10.1515/iupac.76.0294","title":"Metabolic Activation","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; Relation (database); Hazard; Multidisciplinary approach; Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; Biology; Political science; Linguistics; Philosophy","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":[0.0007794679,0.002609354,0.001517701,0.003726769,0.0008212411,0.002919176,0.002179586,0.001733091,0.08503629],"category_scores_gemma":[0.005623172,0.0006589662,0.002260347,0.00589837,0.0003411005,0.001771678,0.001943308,0.00187554,0.08880495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372113,"about_ca_system_score_gemma":0.002088329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01104544,"about_ca_topic_score_gemma":0.02518344,"domain_scores_codex":[0.9988508,0.0001713902,0.0001808497,0.0004671736,0.0002143553,0.0001153509],"domain_scores_gemma":[0.9981236,0.0006489047,0.000288854,0.0004715253,0.0003226785,0.0001444344],"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":[0.0003258126,0.00004199144,0.003434219,0.004400292,0.000135415,0.0000806746,0.00006006787,0.0008767147,0.0005530523,0.001727457,0.9742377,0.0141266],"study_design_scores_gemma":[0.00014418,0.00002516501,0.005134707,0.000806395,0.00007985869,0.0001296701,0.00005223837,0.000341638,0.0004565929,0.002108548,0.9906856,0.00003538386],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001846631,0.0003643099,0.0001467102,0.00004786844,0.00002716496,0.00001439038,0.99755,0.0004317908,0.001233111],"genre_scores_gemma":[0.0004750369,0.0002720527,0.0004830192,0.00007663727,0.000006974234,0.00008100873,0.9978405,0.0000933735,0.0006713987],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08503629,"threshold_uncertainty_score":0.2844747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065367987147783,"score_gpt":0.3661597897666102,"score_spread":0.3555061098951324,"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."}}