{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001459071,0.0004504085,0.0003905236,0.001163907,0.0002566937,0.000791547,0.0003325821,0.000392503,0.0006653408],"category_scores_gemma":[0.005537992,0.0001770363,0.0003653163,0.0009282544,0.000217537,0.0003760827,0.0004584239,0.0004471586,0.0001468173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004665651,"about_ca_system_score_gemma":0.0005980053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01303167,"about_ca_topic_score_gemma":0.02185673,"domain_scores_codex":[0.9989605,0.0004651948,0.0001101926,0.00009186596,0.0002635001,0.0001087671],"domain_scores_gemma":[0.9970738,0.0009875544,0.0008809383,0.0001040279,0.0006308836,0.0003226928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008548859,0.00003528103,0.9977118,0.00001142255,0.00002846704,0.00001424099,0.0000367447,0.00005756486,0.00005247652,0.000003534396,0.00009038967,0.001872675],"study_design_scores_gemma":[0.00001906664,0.0002442322,0.9977371,0.00002226757,0.00002989699,0.0001193503,0.0001415732,0.001343098,0.0001382162,0.00001681268,0.0001827248,0.00000575586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986709,0.0002762108,0.000140968,0.00005517604,0.00000769094,0.0000271561,0.0003250251,0.000010238,0.0004865958],"genre_scores_gemma":[0.9991498,0.00006395917,0.0003887236,0.0000225093,0.000005036375,0.00001635703,0.0002824844,7.770535e-7,0.0000703765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01303167,"threshold_uncertainty_score":0.02591163,"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."}}