{"id":"W4408557574","doi":"10.3390/antibiotics14030314","title":"ICD-10 Codes to Identify Adverse Drug Events Associated with Antibiotics in Administrative Data","year":2025,"lang":"en","type":"article","venue":"Antibiotics","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Coastal Health; Vancouver Coastal Health Research Institute; University of British Columbia; BC Centre for Disease Control","funders":"","keywords":"Medicine; Antibiotics; Medical prescription; Diagnosis code; Intensive care medicine; Confidence interval; Emergency medicine; Adverse effect; Medical emergency; 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":[],"consensus_categories":[],"category_scores_codex":[0.01208338,0.0007268019,0.0008589473,0.009802475,0.0005267431,0.0009537634,0.001223088,0.0005363168,0.00223749],"category_scores_gemma":[0.0419316,0.0003257534,0.001400786,0.008266405,0.0005190411,0.0005884248,0.001637177,0.001217136,0.0006162587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482555,"about_ca_system_score_gemma":0.003028307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01079857,"about_ca_topic_score_gemma":0.01785529,"domain_scores_codex":[0.9809104,0.006363838,0.007420681,0.001012822,0.003592151,0.0007000712],"domain_scores_gemma":[0.9381114,0.02523206,0.02236252,0.005133308,0.008316319,0.0008444024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004073994,0.0003557326,0.9251171,0.0012351,0.000526099,0.0003970662,0.0009897527,0.002646178,0.00165279,0.002503667,0.01327237,0.0508967],"study_design_scores_gemma":[0.0001189493,0.0002533328,0.9687364,0.0005770783,0.0001530298,0.0008173303,0.0006906686,0.007917218,0.002060248,0.002673783,0.01592488,0.00007702283],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5309338,0.003236893,0.2265531,0.0021981,0.0008333206,0.0172166,0.1939641,0.001843549,0.02322046],"genre_scores_gemma":[0.6459159,0.001090563,0.2622582,0.0007172744,0.0002352207,0.008693152,0.07931268,0.0001339044,0.001643137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01208338,"threshold_uncertainty_score":0.06390381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.145571565011298,"score_gpt":0.5046524223868452,"score_spread":0.3590808573755471,"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."}}