{"id":"W4291335400","doi":"10.2196/39782","title":"The Reduction in Medical Errors on Implementing an Intensive Care Information System in a Setting Where a Hospital Electronic Medical Record System is Already in Use: Retrospective Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Perioperative Medicine","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tokyo Women's Medical University","keywords":"Medicine; Incidence (geometry); Medical record; Retrospective cohort study; Intensive care; Emergency medicine; Electronic medical record; Intensive care unit; Pediatrics; Intensive care medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003855959,0.0002874871,0.0003918701,0.002931354,0.000446091,0.0007554232,0.0005577939,0.0003644262,0.0006857632],"category_scores_gemma":[0.01321655,0.0004300958,0.00113437,0.002881528,0.0004715718,0.0009773215,0.0009262299,0.0006492256,0.0001372897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009290582,"about_ca_system_score_gemma":0.001153012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005928022,"about_ca_topic_score_gemma":0.004903288,"domain_scores_codex":[0.9950662,0.001489761,0.001312545,0.0006295359,0.001087517,0.0004144705],"domain_scores_gemma":[0.9707825,0.005531578,0.01784874,0.001362464,0.003657907,0.0008168895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009544291,0.00003120266,0.9987301,0.00002520755,0.00005782306,0.00002982969,0.00008598233,0.00003293754,0.00003425873,0.000005608469,0.00004327737,0.000828434],"study_design_scores_gemma":[0.000004733888,0.0002552806,0.9986872,0.00002353547,0.00006679479,0.0001209549,0.0003518279,0.0001711635,0.000127423,0.000005018006,0.0001810523,0.000004968615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984967,0.0003063744,0.0001890097,0.00002243298,0.000005205911,0.00004529952,0.000664753,0.000004253595,0.0002658805],"genre_scores_gemma":[0.9985269,0.0002550085,0.0002571331,0.0000264066,0.00001066504,0.00004653982,0.0007990183,0.000003112438,0.00007512503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005928022,"threshold_uncertainty_score":0.02039248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152525122199871,"score_gpt":0.4070187006655384,"score_spread":0.3854934494435396,"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."}}