{"id":"W4417183936","doi":"10.1097/cin.0000000000001405","title":"A Machine Learning Approach to Predict Health Care–acquired Urinary Tract Infections From Electronic Nursing Documentation","year":2025,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Urinary Tract Infections Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Documentation; Boosting (machine learning); Electronic health record; Data collection; MEDLINE; Gradient boosting; Urinary system; Missing data","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002888822,0.0003060153,0.0004431704,0.0009903271,0.0006396078,0.000175492,0.0001596555,0.00009508236,0.00001385613],"category_scores_gemma":[0.00003496571,0.0003403162,0.000144853,0.0009664359,0.00007537542,0.0005569335,0.00005709409,0.0005082144,0.00002525843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00320363,"about_ca_system_score_gemma":0.0003614606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001027853,"about_ca_topic_score_gemma":0.00000152901,"domain_scores_codex":[0.9978426,0.0001144216,0.0008147339,0.0002757225,0.000345811,0.0006067226],"domain_scores_gemma":[0.9988866,0.0001165095,0.0002645675,0.0004257834,0.00009922303,0.000207337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005417517,0.02148565,0.01071208,0.00139418,0.0009321934,0.00001482075,0.1022035,0.1693832,0.00005434086,0.006858634,0.01347909,0.6729406],"study_design_scores_gemma":[0.008677475,0.01873255,0.0352578,0.01035608,0.001186476,0.0007054468,0.02109027,0.8493879,0.000249341,0.001161411,0.05200135,0.001193828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09096301,0.0009647116,0.8516978,0.001585695,0.001178024,0.001673229,0.000008448545,0.0005897881,0.05133928],"genre_scores_gemma":[0.9523606,0.00009343217,0.04512757,0.001372348,0.0001537673,0.00006109574,0.0006035161,0.00003418151,0.0001934614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8613976,"threshold_uncertainty_score":0.9999049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027971084563982,"score_gpt":0.2997263995659781,"score_spread":0.2894466887203383,"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."}}