{"id":"W1951380831","doi":"10.1136/amiajnl-2013-002116","title":"ICD-10 codes used to identify adverse drug events in administrative data: a systematic review","year":2013,"lang":"en","type":"review","venue":"Journal of the American Medical Informatics Association","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; Vancouver Coastal Health Research Institute; University of British Columbia; Vancouver Coastal Health","funders":"","keywords":"Coding (social sciences); Medicine; Adverse effect; Diagnosis code; MEDLINE; Set (abstract data type); Computer science; Information retrieval; Data mining; Statistics; 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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.008131742,0.0004174832,0.003351351,0.0003146653,0.0001418147,0.00002791238,0.002227327,0.0002881833,0.0003638677],"category_scores_gemma":[0.007898165,0.0002606226,0.0006547094,0.001174197,0.0001060652,0.0006687343,0.0004153645,0.002795116,0.000579444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013239,"about_ca_system_score_gemma":0.001510817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001912801,"about_ca_topic_score_gemma":0.00003390289,"domain_scores_codex":[0.9916975,0.002510017,0.003655997,0.0001596405,0.001514846,0.000462037],"domain_scores_gemma":[0.9853373,0.00269984,0.01055756,0.0005408399,0.0003473412,0.0005170863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000589328,0.0009606261,0.0005866342,0.5957716,0.005927247,0.00007263314,0.002488828,0.00006630886,0.000004225474,0.00002216331,0.3440679,0.04997287],"study_design_scores_gemma":[0.0007674047,0.00007185694,0.00005549395,0.2618069,0.007426535,0.0001514963,0.0007820031,0.0004203354,0.000003038799,0.00001679889,0.7280735,0.0004246347],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001586455,0.9868472,0.0000507178,0.002995222,0.002570064,0.00492834,0.0005210244,0.0000314899,0.0004695239],"genre_scores_gemma":[0.0002912867,0.9940051,0.00007686242,0.004339345,0.0002867951,0.0001380785,0.00009007187,0.00002664309,0.0007458247],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3840055,"threshold_uncertainty_score":0.9999846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1934403541551048,"score_gpt":0.5454114426251365,"score_spread":0.3519710884700317,"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."}}