{"id":"W3006051952","doi":"10.2196/16073","title":"Detecting Potential Medication Selection Errors During Outpatient Pharmacy Processing of Electronic Prescriptions With the RxNorm Application Programming Interface: Retrospective Observational Cohort Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Michigan","keywords":"Medical prescription; Pharmacy; Pharmacist; Medicine; Observational study; Electronic prescribing; Medical emergency; Computer science; Family medicine; Nursing; 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":[0.001990844,0.0004372704,0.0007628858,0.00114528,0.001036776,0.00114304,0.0008685581,0.0007880909,0.001237664],"category_scores_gemma":[0.007130807,0.0008222555,0.0009731784,0.001836376,0.0004484297,0.001278261,0.001077567,0.001256531,0.000429257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009084854,"about_ca_system_score_gemma":0.001123895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01208829,"about_ca_topic_score_gemma":0.0141319,"domain_scores_codex":[0.9971886,0.0004788719,0.0004700703,0.0007986844,0.0007001756,0.0003636317],"domain_scores_gemma":[0.9929475,0.001064925,0.00375453,0.0006276858,0.001056418,0.0005488904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008452019,0.00007428908,0.9987896,0.00001938481,0.00003573162,0.0000806322,0.0002049705,0.000008090034,0.00007801886,0.000008262384,0.00008753745,0.0005289911],"study_design_scores_gemma":[0.00001586147,0.0004434953,0.9972914,0.00003131401,0.00007147031,0.0004240918,0.00111209,0.0001889619,0.00008413449,0.00001717268,0.0003091196,0.00001092474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989412,0.0001701477,0.0001281473,0.00001920958,0.000004920238,0.00005416324,0.0004662458,0.000003880584,0.0002121177],"genre_scores_gemma":[0.9986236,0.0001819049,0.000234533,0.00007757102,0.00001164399,0.00007476391,0.0006457714,0.000007158028,0.0001429496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01208829,"threshold_uncertainty_score":0.02403587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04076854217415557,"score_gpt":0.4040701451018504,"score_spread":0.3633016029276948,"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."}}