{"id":"W2028232434","doi":"10.2165/00002018-200831110-00005","title":"Detection of Adverse Drug Events and Other Treatment Outcomes Using an Electronic Prescribing System","year":2008,"lang":"en","type":"article","venue":"Drug Safety","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Discontinuation; Medicine; Medical prescription; Drug; Adverse effect; Electronic prescribing; Medical record; Intensive care medicine; Gold standard (test); Emergency medicine; 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":[0.001100925,0.0002469683,0.0005718129,0.0001395774,0.0009441292,0.000001105551,0.000111204,0.0001445096,0.00002431627],"category_scores_gemma":[0.00003664755,0.0002036145,0.00009038688,0.0001754478,0.00003765574,0.0001789732,0.00003936566,0.0003610048,0.00002659453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002677907,"about_ca_system_score_gemma":0.0008544636,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0179555,"about_ca_topic_score_gemma":0.01001816,"domain_scores_codex":[0.996145,0.00139349,0.0009326945,0.0003812951,0.0002620842,0.0008854987],"domain_scores_gemma":[0.9984831,0.0002974135,0.0004998932,0.0004364554,0.00008955479,0.0001936414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004444965,0.0003304457,0.9601648,0.001618955,0.0002463124,0.000008781342,0.02945497,0.0002509546,0.003496983,0.001314171,0.00002707982,0.002641981],"study_design_scores_gemma":[0.03089062,0.002475348,0.7411413,0.005490343,0.0007901124,0.0004700806,0.07173087,0.05218015,0.008588823,0.0002956817,0.08301868,0.002927973],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956173,0.0004365092,0.0006376255,0.00008106788,0.0005511665,0.001786215,0.00002879817,0.0001549454,0.0007064239],"genre_scores_gemma":[0.998183,0.00007405419,0.0001005536,0.00006847477,0.0001699989,0.0001029049,0.000005501246,0.00005720408,0.001238314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2190236,"threshold_uncertainty_score":0.988584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06250692843296986,"score_gpt":0.3778822500356059,"score_spread":0.3153753216026361,"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."}}