{"id":"W3006136946","doi":"","title":"Quality of electronic records documenting adverse drug reactions within a hospital setting: identification of discrepancies and information completeness.","year":2019,"lang":"en","type":"article","venue":"PubMed","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Documentation; Drug allergy; Medical record; Electronic data; Medical emergency; Allergy; Drug reaction; Patient safety; Electronic medical record; Pediatrics; Drug; Health care; Database; Internal medicine; Pharmacology","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":[0.06174779,0.0003336673,0.0009330863,0.005836999,0.0006662157,0.003228347,0.001173376,0.0009319112,0.0006307572],"category_scores_gemma":[0.2240172,0.000457969,0.0007428341,0.007068747,0.001019463,0.002619315,0.002507834,0.000739641,0.0002610315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695604,"about_ca_system_score_gemma":0.001768773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00288933,"about_ca_topic_score_gemma":0.002095574,"domain_scores_codex":[0.8957878,0.04356072,0.02934158,0.004859762,0.02538759,0.001062617],"domain_scores_gemma":[0.5362684,0.2277555,0.1701768,0.02261311,0.04141436,0.001771819],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004324494,0.00007213418,0.9444281,0.0009556653,0.0003052907,0.000144179,0.002393921,0.0004378609,0.0006912232,0.0001200951,0.0006350045,0.04938413],"study_design_scores_gemma":[0.00002901198,0.0006434089,0.987335,0.0009793603,0.0002173435,0.001243979,0.002241167,0.001437425,0.001789281,0.0003025454,0.003727735,0.00005377607],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744905,0.01030245,0.007859521,0.001389214,0.0001210429,0.0003114615,0.002769043,0.0001455388,0.00261124],"genre_scores_gemma":[0.9917731,0.001170355,0.004877708,0.0002659324,0.00007995885,0.00009120569,0.001502784,0.00001727879,0.0002218346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9382522,"threshold_uncertainty_score":0.3265574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04190541110700233,"score_gpt":0.3613716452329848,"score_spread":0.3194662341259824,"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."}}