{"id":"W4387172024","doi":"10.1007/978-981-99-5162-8_4","title":"Bioinformatic Tools for Clinical Metabolomics","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Metabolomics; Identification (biology); Biomarker discovery; Metabolome; Disease; Computational biology; Biomarker; Data science; Computer science; Bioinformatics; Medicine; Biology; Proteomics; Pathology","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":[0.001367244,0.001709064,0.001016083,0.002247917,0.0004161221,0.003122422,0.001654782,0.001022065,0.02345258],"category_scores_gemma":[0.002540189,0.0006819417,0.0007736934,0.002508461,0.0009834316,0.003242546,0.001649666,0.002593834,0.02084526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007527249,"about_ca_system_score_gemma":0.0005410621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000509349,"about_ca_topic_score_gemma":0.0006502219,"domain_scores_codex":[0.9994011,0.00011974,0.00004263903,0.00008833049,0.0003214834,0.00002679489],"domain_scores_gemma":[0.9990813,0.000595971,0.00003778784,0.00009479916,0.0001592151,0.00003102817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003811927,0.00005649448,0.0001510129,0.0009696633,0.0000557643,0.0001683609,0.0001086386,0.002219907,0.006388009,0.2028928,0.1849583,0.601993],"study_design_scores_gemma":[0.00001020528,0.00001842951,0.0003060089,0.0002773449,0.00002499877,0.000685486,0.00003833169,0.008403121,0.003099249,0.2949483,0.6921567,0.00003182601],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006164981,0.04344228,0.873277,0.003422105,0.001724983,0.0001000906,0.001270148,0.008580248,0.06756668],"genre_scores_gemma":[0.008676801,0.04001858,0.859237,0.002904828,0.001794591,0.0002881938,0.003175736,0.002314962,0.08158932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02345258,"threshold_uncertainty_score":0.0784567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030156714174623,"score_gpt":0.3436510009045063,"score_spread":0.240635329487044,"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."}}