{"id":"W4388009567","doi":"10.1016/j.ekir.2023.10.019","title":"Clinical Decision Support Tools in the Electronic Medical Record","year":2023,"lang":"en","type":"article","venue":"Kidney International Reports","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Orthopaedic Innovation Centre","funders":"Johns Hopkins University","keywords":"Interoperability; Medicine; System integration; Clinical decision support system; Electronic medical record; Decision support system; Medical record; Knowledge management; Risk analysis (engineering); Medical emergency; Computer science; Data mining; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02672279,0.0005621127,0.0008054667,0.006233409,0.001315353,0.009562854,0.00235646,0.0026441,0.01354129],"category_scores_gemma":[0.143554,0.0006064539,0.001323426,0.0102068,0.001561079,0.0148604,0.004843146,0.003619862,0.008131494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002813064,"about_ca_system_score_gemma":0.007778178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003441039,"about_ca_topic_score_gemma":0.003739006,"domain_scores_codex":[0.9549788,0.02281931,0.00909514,0.001787636,0.01036917,0.000949931],"domain_scores_gemma":[0.8239054,0.122584,0.01371073,0.01197691,0.02462192,0.003201018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001156354,0.0001651427,0.01167495,0.00360888,0.0001278261,0.0005733672,0.003119851,0.0005474485,0.0005582763,0.02549499,0.13395,0.8200637],"study_design_scores_gemma":[0.00007306859,0.0001895376,0.01040136,0.01170092,0.0001822237,0.0016574,0.002442199,0.001597877,0.001373763,0.01587627,0.954334,0.0001714111],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04163407,0.2024163,0.1742041,0.2489108,0.01550006,0.003179937,0.01441188,0.007756919,0.2919859],"genre_scores_gemma":[0.244019,0.16708,0.4678137,0.05819055,0.01143592,0.001778739,0.01272862,0.001061149,0.03589223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02672279,"threshold_uncertainty_score":0.1413253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059010910856382,"score_gpt":0.5253232429682684,"score_spread":0.4194221518826302,"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."}}