{"id":"W4400982565","doi":"10.14309/ajg.0000000000002978","title":"Deep Learning Model Using Stool Pictures for Predicting Endoscopic Mucosal Inflammation in Patients With Ulcerative Colitis","year":2024,"lang":"en","type":"article","venue":"The American Journal of Gastroenterology","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital","funders":"Ministry of Science and ICT, South Korea","keywords":"Medicine; Ulcerative colitis; Mucosal inflammation; Gastroenterology; Internal medicine; Inflammation; Colitis; Endoscopy; Disease","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":[0.0008814264,0.0007034751,0.0006528738,0.0008875305,0.0001782057,0.0005553492,0.0004705882,0.0006531383,0.001058093],"category_scores_gemma":[0.002023858,0.0001985685,0.0007026888,0.0004317856,0.0001495911,0.0003872344,0.0005348205,0.0007016466,0.0003515316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004699444,"about_ca_system_score_gemma":0.0005714246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006519645,"about_ca_topic_score_gemma":0.005001413,"domain_scores_codex":[0.9996529,0.0001045315,0.00003598908,0.00008528315,0.00005153432,0.00006986145],"domain_scores_gemma":[0.9994255,0.0002317676,0.00009774605,0.00003006227,0.0001544338,0.00006056626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001654069,0.001222826,0.5323182,0.0001980127,0.0005558307,0.0005865462,0.000111388,0.1658732,0.004117121,0.0002480353,0.007366149,0.2857487],"study_design_scores_gemma":[0.00005149987,0.0004357779,0.03183737,0.00004407892,0.0001081969,0.0001404496,0.00005780466,0.9653669,0.001065596,0.0003333949,0.0005400933,0.00001892599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961672,0.001542439,0.03225284,0.0008809405,0.0001576861,0.0001068971,0.001378312,0.0004269296,0.001581871],"genre_scores_gemma":[0.9910982,0.0002629114,0.006560834,0.0001204356,0.00003921283,0.00006032954,0.001215574,0.000006990047,0.0006355473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006519645,"threshold_uncertainty_score":0.01296341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005028192699540146,"score_gpt":0.2339605083534332,"score_spread":0.2289323156538931,"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."}}