{"id":"W4317545889","doi":"10.1093/ibd/izac281","title":"Serum Lipidomic Screen Identifies Key Metabolites, Pathways, and Disease Classifiers in Crohn’s Disease","year":2023,"lang":"en","type":"article","venue":"Inflammatory Bowel Diseases","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Université de Montréal; Hôpital Maisonneuve-Rosemont; McGill University Health Centre; Montreal Heart Institute","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Lipidomics; Lipidome; Sphingomyelin; Disease; Crohn's disease; Metabolomics; Inflammatory bowel disease; Inflammation; Dysbiosis; Medicine; Lipid metabolism; Phosphatidylethanolamine; Cholesterol; Biology; Biochemistry; Bioinformatics; Internal medicine; Phosphatidylcholine; Phospholipid","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":[0.0007525807,0.0006183703,0.0005324919,0.001198095,0.0002302783,0.000682038,0.0001761363,0.0003958013,0.0006929556],"category_scores_gemma":[0.0009922264,0.00013789,0.0005053,0.0007351492,0.0001900159,0.000222547,0.0004371323,0.0003752071,0.0002826621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002520903,"about_ca_system_score_gemma":0.0003094391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005745824,"about_ca_topic_score_gemma":0.001021834,"domain_scores_codex":[0.9996258,0.00008177963,0.00003937076,0.0001223104,0.00008467167,0.00004600876],"domain_scores_gemma":[0.9994746,0.0001751691,0.0001427245,0.00004578878,0.00009407145,0.00006757431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002906142,0.0003030551,0.6082979,0.0002308388,0.0003905881,0.0003957988,0.0001171785,0.001858829,0.3442149,0.00007856822,0.0004143184,0.0407919],"study_design_scores_gemma":[0.0001080659,0.002176584,0.8583858,0.00006431397,0.0007222492,0.001558428,0.0002152754,0.01647804,0.1177334,0.0005347222,0.001981689,0.00004133311],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942805,0.0008952415,0.003301995,0.00009793013,0.00001091586,0.00004008839,0.0009493675,0.0001066347,0.0003174459],"genre_scores_gemma":[0.9926898,0.0003485933,0.005257622,0.00008493548,0.00001473156,0.00003266271,0.001336525,0.00001307581,0.0002221509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001198095,"threshold_uncertainty_score":0.0039801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0120715240433288,"score_gpt":0.2334584224698108,"score_spread":0.221386898426482,"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."}}