{"id":"W2117586793","doi":"10.1136/bmjqs-2014-003555","title":"Computerised physician order entry-related medication errors: analysis of reported errors and vulnerability testing of current systems","year":2015,"lang":"en","type":"article","venue":"BMJ Quality & Safety","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Patient Safety Foundation","keywords":"Medicine; Order entry; Computerized physician order entry; Vulnerability (computing); Order (exchange); Medical emergency; Vulnerability assessment; Family medicine; Nursing; Computer security; Health care; Computer science; Psychological intervention","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01188801,0.0002983897,0.0004043421,0.007131226,0.0004643095,0.001345078,0.0006786453,0.0004333693,0.0007290575],"category_scores_gemma":[0.09025098,0.0003038574,0.0009068132,0.005116748,0.0007821624,0.002518358,0.001881653,0.0005053347,0.0001998431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001291174,"about_ca_system_score_gemma":0.001390767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004256369,"about_ca_topic_score_gemma":0.003950922,"domain_scores_codex":[0.9848332,0.005144109,0.003518936,0.001204663,0.004852965,0.0004460728],"domain_scores_gemma":[0.8232366,0.09976602,0.05066456,0.005458038,0.01995114,0.0009235757],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001312762,0.00007717237,0.972587,0.0004238911,0.0001376137,0.0002795727,0.00570725,0.0005813475,0.0006154543,0.0001655529,0.0002389363,0.01905489],"study_design_scores_gemma":[0.000009241046,0.0005217028,0.9845365,0.0002981239,0.0001086541,0.0008850751,0.005483489,0.005507561,0.00136553,0.000218203,0.00103139,0.00003466267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958974,0.0004954264,0.001673736,0.0001410324,0.000006656029,0.0001937743,0.0007677895,0.00004126216,0.0007829231],"genre_scores_gemma":[0.996542,0.0002396629,0.002515377,0.00003068925,0.000006046427,0.00008488716,0.0004573348,0.000009658726,0.0001142731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.988112,"threshold_uncertainty_score":0.06287056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2456465161444839,"score_gpt":0.5207096990166359,"score_spread":0.2750631828721519,"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."}}