{"id":"W2902939883","doi":"10.1136/bmjhci-2019-100086","title":"Evaluating a post-implementation electronic medical record training intervention for diabetes management in primary care","year":2019,"lang":"en","type":"article","venue":"BMJ Health & Care Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Victoria; Island Health","funders":"University of Victoria","keywords":"Medicine; Electronic medical record; Intervention (counseling); Medical record; Health informatics; Best practice; Diabetes management; Health care; Multimedia; Diabetes mellitus; Medical education; Nursing; Medical emergency; Computer science; Type 2 diabetes; Public health; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00993661,0.0007920008,0.0008813534,0.0006369532,0.001221369,0.0009531807,0.001518713,0.001683984,0.006966444],"category_scores_gemma":[0.02485417,0.0006082864,0.0011593,0.0003756212,0.0005107326,0.001277117,0.001579723,0.001827161,0.0005319035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002570419,"about_ca_system_score_gemma":0.006950276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002731476,"about_ca_topic_score_gemma":0.005621857,"domain_scores_codex":[0.9918358,0.004872144,0.000661301,0.0006585014,0.0009664249,0.001005839],"domain_scores_gemma":[0.9859152,0.007653388,0.002011032,0.0008501222,0.0012285,0.002341749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"nonrandomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.04987134,0.4725735,0.01936374,0.00415267,0.0007804733,0.0001915747,0.003887375,0.001513852,0.003574356,0.0003618009,0.00295041,0.4407789],"study_design_scores_gemma":[0.09161761,0.6913325,0.196952,0.001101484,0.001447031,0.0001000132,0.002361761,0.003011039,0.00569165,0.0002799146,0.006010823,0.00009425515],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829229,0.0001790159,0.0008659331,0.0005056148,0.0001531843,0.01298694,0.0002220967,0.00013364,0.00203075],"genre_scores_gemma":[0.9606763,0.0003198097,0.0139641,0.0007228767,0.0001452162,0.02191043,0.0003005856,0.00001591414,0.00194476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00993661,"threshold_uncertainty_score":0.05255049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07994871885263082,"score_gpt":0.5302724441638208,"score_spread":0.45032372531119,"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."}}