{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001698459,0.0001261476,0.0002451531,0.0001455766,0.0001188725,0.00001240767,0.0001227761,0.00008269559,0.00005040292],"category_scores_gemma":[0.0001860627,0.0001280532,0.00008636217,0.0002397159,0.0001243036,0.001306156,0.0000531414,0.0003421012,0.00001729917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007856889,"about_ca_system_score_gemma":0.00006384773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001447147,"about_ca_topic_score_gemma":0.00001670878,"domain_scores_codex":[0.9983492,0.0001954866,0.0008113547,0.0001678633,0.0001665454,0.0003095614],"domain_scores_gemma":[0.9983931,0.0002496288,0.0009567048,0.0001690958,0.0001499735,0.00008149078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001042707,0.001059566,0.736436,0.001877149,0.001125365,0.000001381027,0.009300856,0.004962688,0.1496915,0.04356049,0.001347105,0.04959517],"study_design_scores_gemma":[0.002788531,0.00003869031,0.8279441,0.00002558984,0.0002203009,0.000008125606,0.004259434,0.002798868,0.08962905,0.001100725,0.07079892,0.0003876578],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948891,0.00006878882,0.00005242254,0.0005744952,0.0007765164,0.0008717676,0.0001064797,0.00005017321,0.002610216],"genre_scores_gemma":[0.9986675,0.0001795581,0.00003025648,0.0001177473,0.00003902701,0.0002807856,0.0000758639,0.000007746058,0.0006014911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09150809,"threshold_uncertainty_score":0.5221856,"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."}}