{"id":"W4280607179","doi":"10.1093/nar/gkac313","title":"BioTransformer 3.0—a web server for accurately predicting metabolic transformation products","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":196,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Environmental Health Sciences; Genome Canada; Canadian Institutes of Health Research; National Institutes of Health; Alberta Machine Intelligence Institute","keywords":"Xenobiotic; In silico; Transformation (genetics); JSON; Biology; Computational biology; Web server; Table (database); Computer science; Metabolite; Biotransformation; Database; Biochemistry; Enzyme; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001395959,0.003718692,0.001991276,0.001684178,0.0006224037,0.002170865,0.002735102,0.001593955,0.03121336],"category_scores_gemma":[0.002333134,0.001358486,0.00263288,0.001263252,0.0003253431,0.001916149,0.001325358,0.001920477,0.03493753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009026866,"about_ca_system_score_gemma":0.002262295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004630639,"about_ca_topic_score_gemma":0.005558358,"domain_scores_codex":[0.9993318,0.00007918387,0.00006540165,0.0001943567,0.000253501,0.00007571834],"domain_scores_gemma":[0.999175,0.0002363411,0.0001152589,0.0001592721,0.0002231953,0.00009083268],"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":[0.003795909,0.000634159,0.01458294,0.003257012,0.0008606181,0.001110922,0.0001707485,0.06337947,0.08051178,0.006577356,0.6625872,0.1625319],"study_design_scores_gemma":[0.0008955506,0.0005212315,0.006923207,0.0002214065,0.0002219503,0.0007703361,0.00008724944,0.6317091,0.1200904,0.01213463,0.2260293,0.0003956534],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.02121228,0.001240568,0.1766759,0.0003568104,0.000262781,0.0003917592,0.1783935,0.6111408,0.01032546],"genre_scores_gemma":[0.08531776,0.0015435,0.3013211,0.0006702918,0.00009690018,0.001084642,0.5524188,0.04539696,0.01215008],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.03121336,"threshold_uncertainty_score":0.1044191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06809016634241508,"score_gpt":0.349330631081474,"score_spread":0.2812404647390589,"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."}}