{"id":"W2052084025","doi":"10.1007/bf03261973","title":"Incidence and Economic Burden of Adverse Drug Reactions among Elderly Patients in Ontario Emergency Departments","year":2012,"lang":"en","type":"article","venue":"Drug Safety","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; St. Michael's Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Medicine; Polypharmacy; Incidence (geometry); Emergency department; Emergency medicine; Pharmacy; Population; Retrospective cohort study; Logistic regression; Diagnosis code; Health care; Pediatrics; Family medicine; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005092331,0.000213032,0.0002738357,0.0001529648,0.0001885726,0.000002487092,0.0001637695,0.0001215788,0.001797564],"category_scores_gemma":[0.00002625451,0.0002293888,0.00009123822,0.0001194212,0.0001247137,0.0007805311,0.00009249293,0.000640702,0.0001534734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004070122,"about_ca_system_score_gemma":0.0001159416,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03988556,"about_ca_topic_score_gemma":0.06538633,"domain_scores_codex":[0.9983805,0.0001955573,0.000586614,0.0002595762,0.0001098002,0.0004679898],"domain_scores_gemma":[0.9990889,0.0001531497,0.0002680731,0.0001790673,0.00004184304,0.0002689822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001457268,0.0003220958,0.9908458,0.00002308696,0.00008467538,0.000003061113,0.004402105,0.001342207,0.0006052612,0.0001239985,0.001431294,0.000670706],"study_design_scores_gemma":[0.001726304,0.00001744735,0.8966894,0.00001748819,0.0001087792,0.000003387814,0.0006347537,0.0003427478,0.001797233,0.00007218881,0.09834234,0.0002479909],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887334,0.0001094988,0.000002838396,0.0001028662,0.001803027,0.0004133125,0.0001057921,0.00003237136,0.008696939],"genre_scores_gemma":[0.9962791,0.0006965015,0.00003537984,0.00007405123,0.0001241733,0.00004801856,0.00007654936,0.00001698321,0.002649292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09691105,"threshold_uncertainty_score":0.9991149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744386741267191,"score_gpt":0.3582969599565819,"score_spread":0.32085309254391,"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."}}