{"id":"W3177828927","doi":"10.1093/crocol/otab043","title":"Using Patient Completed Screening Tools to Predict Risk of Malnutrition in Patients With Inflammatory Bowel Disease","year":2021,"lang":"en","type":"article","venue":"Crohn s & Colitis 360","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Alexandra Hospital; University of Alberta; University of Calgary","funders":"University Hospital Foundation; Government of Alberta","keywords":"Malnutrition; Medicine; Ulcerative colitis; Inflammatory bowel disease; Body mass index; Internal medicine; Receiver operating characteristic; Gold standard (test); Ambulatory; Crohn's disease; Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001279449,0.0001427983,0.0003135246,0.0002137633,0.0001075946,0.00002676369,0.00004702161,0.00005566372,0.0001182854],"category_scores_gemma":[0.0002048842,0.0001481514,0.00006021885,0.0003395771,0.00005897734,0.0001298097,0.00005696743,0.0002035395,0.000004675323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001745024,"about_ca_system_score_gemma":0.0002482948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007551256,"about_ca_topic_score_gemma":0.00004668935,"domain_scores_codex":[0.998293,0.0001316173,0.0005227918,0.0002937113,0.0004203218,0.0003385518],"domain_scores_gemma":[0.9986086,0.00006301165,0.0001642516,0.000284621,0.000460039,0.0004194269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002701375,0.0004537134,0.9909432,0.0007295983,0.00002683901,0.000256929,0.0002461774,0.0001320778,0.00007993447,0.00009731249,0.0002974013,0.004035474],"study_design_scores_gemma":[0.004918235,0.0002587113,0.9888594,0.002807674,0.00006841754,0.000006169891,0.0001789366,0.0009150135,0.000219407,0.00006273986,0.001563675,0.0001416534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996849,0.0001962927,0.0009415098,0.0002576227,0.00008862212,0.001023132,0.0004239716,0.00004088184,0.0001789795],"genre_scores_gemma":[0.991469,0.00002842795,0.007203721,0.0008563217,0.0000704918,0.00005146883,0.00027714,0.00002659064,0.00001686062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006262211,"threshold_uncertainty_score":0.6041439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03723981018318229,"score_gpt":0.2898548382395403,"score_spread":0.252615028056358,"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."}}