{"id":"W4391873680","doi":"10.1093/jcag/gwad061.260","title":"A260 ADVANCING INFLAMMATORY BOWEL DISEASE DIAGNOSIS THROUGH STOOL PROTEOMIC SIGNATURES OBTAINED VIA DIA-MASS SPECTROMETRY AND MACHINE LEARNING","year":2024,"lang":"en","type":"article","venue":"Journal of the Canadian Association of Gastroenterology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Inflammatory bowel disease; Mass spectrometry; Disease; Medicine; Gastroenterology; Internal medicine; Chromatography; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00160218,0.0008691383,0.0006321194,0.001702163,0.0003165941,0.001025134,0.0003141422,0.0004730961,0.001174369],"category_scores_gemma":[0.00214501,0.0001980716,0.0007103382,0.001118065,0.0002335987,0.0004853924,0.0004688418,0.0005457664,0.0006744997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000305358,"about_ca_system_score_gemma":0.0004495378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001135093,"about_ca_topic_score_gemma":0.001355313,"domain_scores_codex":[0.9995378,0.0001095048,0.00004750106,0.0001410261,0.0001129867,0.00005115548],"domain_scores_gemma":[0.9992482,0.0002521573,0.0001758446,0.00006332736,0.0002013131,0.00005919874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002460989,0.001188719,0.4729092,0.0008428035,0.000732451,0.0009163417,0.0002058202,0.03302913,0.2403764,0.0006422146,0.004213914,0.2424821],"study_design_scores_gemma":[0.00006719929,0.001117041,0.367872,0.0001342169,0.0003888207,0.00107244,0.0002346784,0.5359814,0.08723462,0.001694036,0.00411273,0.00009090244],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9469997,0.002189966,0.04662628,0.0002680752,0.0000807297,0.0001051235,0.001762204,0.0005414266,0.001426484],"genre_scores_gemma":[0.9602258,0.0007307189,0.03620594,0.00009581033,0.00004189517,0.00006895303,0.001963004,0.00003813799,0.0006297944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001702163,"threshold_uncertainty_score":0.008473277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004523910839270349,"score_gpt":0.225508911045688,"score_spread":0.2209850002064176,"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."}}