{"id":"W4280614385","doi":"10.1093/ibd/izac102","title":"High Prevalence of Malnutrition and Micronutrient Deficiencies in Patients With Inflammatory Bowel Disease Early in Disease Course","year":2022,"lang":"en","type":"article","venue":"Inflammatory Bowel Diseases","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health","keywords":"Malnutrition; Medicine; Micronutrient; Micronutrient deficiency; Inflammatory bowel disease; Disease; Crohn's disease; Cohort; Odds ratio; Pediatrics; Internal medicine; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002941669,0.0004836569,0.0002973936,0.0003435304,0.0002226299,0.00004650312,0.0004860958,0.00008456286,0.00007692151],"category_scores_gemma":[0.0001478583,0.0005189801,0.0001466199,0.0002231632,0.0005348928,0.00007958027,0.0005223251,0.0002365633,0.000004738673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001537497,"about_ca_system_score_gemma":0.0007242781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001655731,"about_ca_topic_score_gemma":0.00003650196,"domain_scores_codex":[0.9964923,0.0003957866,0.0007652824,0.0009156557,0.0007969108,0.0006340785],"domain_scores_gemma":[0.9979156,0.00003901869,0.0003637627,0.0008462981,0.000184737,0.0006505593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008714772,0.001450656,0.9832565,0.00125005,0.00003694487,0.0006364182,0.0001552934,0.003586392,0.000412524,0.0003027957,0.0001309365,0.00006676116],"study_design_scores_gemma":[0.004669788,0.0002405248,0.9934095,0.0002156595,0.0001347224,0.000001309916,0.0001407402,0.00008810435,0.0000807786,0.0002479444,0.0001526837,0.0006182334],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994017,0.00243283,0.000007040909,0.00005524466,0.000131795,0.001437621,0.001867932,0.00004074589,0.00000977489],"genre_scores_gemma":[0.9984253,0.0001447394,0.00003255183,0.0001265264,0.00006082679,0.0006859366,0.0003961986,0.00007211658,0.00005580055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01015306,"threshold_uncertainty_score":0.9997262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003342995426933496,"score_gpt":0.1911601335571726,"score_spread":0.1878171381302391,"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."}}