{"id":"W4221125077","doi":"10.2196/35190","title":"Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Medicine; Context (archaeology); Observational study; Propensity score matching; Medical prescription; Pipeline (software); Lasso (programming language); Retrospective cohort study; Medical record; Internal medicine; Computer science; Pharmacology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005486069,0.0003567597,0.0006181104,0.002272975,0.000373367,0.001022633,0.0007204593,0.0005066944,0.001150235],"category_scores_gemma":[0.01472184,0.0002148279,0.001268975,0.004451707,0.0002734947,0.0003908694,0.001012494,0.0006721331,0.0002230307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004514004,"about_ca_system_score_gemma":0.001382367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003999009,"about_ca_topic_score_gemma":0.006018077,"domain_scores_codex":[0.9953081,0.001686865,0.0009009183,0.001247204,0.0006737542,0.0001831593],"domain_scores_gemma":[0.9858246,0.005890178,0.005513702,0.001569183,0.0008470112,0.0003554909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004340833,0.00006834348,0.9843867,0.0002735281,0.0008365207,0.0001869308,0.00006138629,0.001124006,0.000656304,0.0002511371,0.001354262,0.01036675],"study_design_scores_gemma":[0.0001460225,0.0003416406,0.9824427,0.0001343537,0.000863673,0.0005474208,0.0001532516,0.007827425,0.0008973479,0.000524178,0.006092296,0.00002967819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9501565,0.00159998,0.008982033,0.0004869655,0.00003075318,0.0003614071,0.03728752,0.00007667446,0.001018026],"genre_scores_gemma":[0.9581779,0.0006073858,0.009404877,0.0002396042,0.00006516052,0.0002810832,0.03096931,0.0000194071,0.0002352774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005486069,"threshold_uncertainty_score":0.02901345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02862055378249543,"score_gpt":0.3877781869801138,"score_spread":0.3591576331976183,"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."}}