{"id":"W3155338345","doi":"10.1186/s12913-021-06346-y","title":"Detection of adverse drug events in e-prescribing and administrative health data: a validation study","year":2021,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; McGill University; McGill University Health Centre","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Gold standard (test); Adverse effect; Diagnosis code; Emergency medicine; Antidepressant; Drug; Prospective cohort study; Health care; Internal medicine; Psychiatry; Population","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":[0.04929998,0.001139979,0.0008003276,0.001993302,0.0009641061,0.001681994,0.002312018,0.001821612,0.0009223726],"category_scores_gemma":[0.09842567,0.0008479499,0.002144309,0.001968438,0.002025902,0.001609186,0.002246539,0.001578626,0.0006781924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001085466,"about_ca_system_score_gemma":0.002433267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006141735,"about_ca_topic_score_gemma":0.005334527,"domain_scores_codex":[0.956118,0.02975963,0.00318709,0.003337477,0.006331362,0.001266423],"domain_scores_gemma":[0.8467043,0.07291663,0.02946404,0.02852526,0.01943636,0.002953347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008492743,0.0009156103,0.9928864,0.00006209651,0.0002660027,0.00007889984,0.0003893198,0.0002505809,0.0002996439,0.00005077728,0.000164001,0.003787422],"study_design_scores_gemma":[0.0004087279,0.001834582,0.9924498,0.00008494523,0.0002413303,0.0004781327,0.0002861764,0.002737587,0.0005430572,0.0001077782,0.0007996249,0.00002821377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995423,0.0001568475,0.001992712,0.00008193827,0.00002118694,0.00076507,0.0008742991,0.00001914853,0.0006656483],"genre_scores_gemma":[0.9925121,0.0001035111,0.00354929,0.0001908273,0.00004473034,0.0005087326,0.00291487,0.00001558369,0.0001604688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04929998,"threshold_uncertainty_score":0.2607263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3951830884829906,"score_gpt":0.5966214590806832,"score_spread":0.2014383705976926,"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."}}