{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008384952,0.0003614219,0.0004661822,0.0003400482,0.0002941104,0.00003160359,0.0008495446,0.0002841764,0.000302346],"category_scores_gemma":[0.0003922188,0.0003514414,0.00006987333,0.00122964,0.0002122211,0.0003860416,0.000368611,0.0009423736,0.0003296538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001780176,"about_ca_system_score_gemma":0.0004310347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004818433,"about_ca_topic_score_gemma":0.001093199,"domain_scores_codex":[0.997502,0.0003583468,0.0005214698,0.000686524,0.0002472232,0.0006844114],"domain_scores_gemma":[0.9981462,0.0006040983,0.0001930114,0.0006357023,0.0001703785,0.0002505973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001253277,0.004085621,0.8234863,0.0001952584,0.001783296,0.0007439267,0.001252789,0.004680728,0.03947064,0.001948793,0.1193568,0.0017425],"study_design_scores_gemma":[0.01144516,0.0003573578,0.5247751,0.001326134,0.001816703,0.00003009018,0.003469508,0.01328151,0.2104503,0.0005413403,0.2305461,0.001960674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821689,0.0001007145,0.0001762052,0.002008589,0.001194386,0.0008177386,0.001174893,0.000148321,0.01221023],"genre_scores_gemma":[0.9885947,0.0001945345,0.0002479562,0.002526374,0.00008559929,7.606405e-7,0.0006128787,0.00003040097,0.007706762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2987113,"threshold_uncertainty_score":0.9998938,"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."}}