{"id":"W4304117487","doi":"10.1093/nar/gkac868","title":"MiMeDB: the Human Microbial Metabolome Database","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; Genome Canada; Canadian Institutes of Health Research; National Institutes of Health; Canada Foundation for Innovation","keywords":"Metabolome; Exposome; Biology; Microbiome; Human Microbiome Project; Metagenomics; Human microbiome; Human health; Genome; Computational biology; Microbial metabolism; Microbial ecology; Metabolomics; Bacteria; Genetics; Bioinformatics; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002249437,0.0001463829,0.000176203,0.0001466293,0.001849955,0.00005961759,0.0009608272,0.00005232977,0.001010065],"category_scores_gemma":[0.0001846212,0.0001122242,0.0001152728,0.0004962281,0.0003550852,0.000003779723,0.002462962,0.0006336793,0.00005175998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003980507,"about_ca_system_score_gemma":0.00009297351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009180532,"about_ca_topic_score_gemma":0.00002905217,"domain_scores_codex":[0.9975321,0.0005585848,0.0002036802,0.0004966167,0.0006044626,0.0006045182],"domain_scores_gemma":[0.9988281,0.00004117593,0.000045624,0.000865331,0.0001326042,0.00008713674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000510099,0.00009548759,0.0006943889,0.000006341947,0.00009549048,0.000007305668,0.0000783238,0.000003799753,0.9115376,0.003112563,0.08359113,0.0007265204],"study_design_scores_gemma":[0.0004811209,0.0002990734,0.001831563,0.000001214341,0.00001523099,0.0000227485,0.0006972709,0.000009058544,0.08099233,0.0003506752,0.9151405,0.0001591959],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985853,0.003152837,0.0000442184,0.001747357,0.0002459245,0.000365451,0.000185922,0.00001555062,0.008389737],"genre_scores_gemma":[0.9880427,0.0003951388,0.0003713509,0.0003914058,0.0004664485,0.0001672404,0.0002136129,0.00003794886,0.009914132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8315494,"threshold_uncertainty_score":0.9999031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04698035397063809,"score_gpt":0.3454578879005448,"score_spread":0.2984775339299067,"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."}}