{"id":"W3112236753","doi":"10.1111/epi.16738","title":"Primary care electronic medical records can be used to predict risk and identify potentially modifiable factors for early and late death in adult onset epilepsy","year":2020,"lang":"en","type":"article","venue":"Epilepsia","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Hotchkiss Brain Institute; University of Calgary; University of Alberta","funders":"","keywords":"Medicine; Brier score; Confidence interval; Receiver operating characteristic; Population; Logistic regression; Epilepsy; Odds ratio; Cohort; Observational study; Pediatrics; Internal medicine; Machine learning; Psychiatry","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":[0.007570836,0.0003923983,0.0005241201,0.002179663,0.0002950896,0.001145632,0.0005031034,0.0006394656,0.00124469],"category_scores_gemma":[0.04303657,0.0003540696,0.0007127153,0.002017485,0.0003087687,0.0008829365,0.0007695694,0.0004334108,0.0004656288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000486531,"about_ca_system_score_gemma":0.0005907234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003486611,"about_ca_topic_score_gemma":0.007051235,"domain_scores_codex":[0.9959148,0.002274021,0.000422046,0.0004470621,0.000769814,0.0001722592],"domain_scores_gemma":[0.9781997,0.01164225,0.006714218,0.001388483,0.001835546,0.0002198039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001763168,0.00005482835,0.9775938,0.0001087629,0.0001625465,0.00004591241,0.0001034986,0.000586633,0.0001038522,0.00005354217,0.0006316079,0.02037864],"study_design_scores_gemma":[0.00005679183,0.0002845868,0.9868985,0.0002039102,0.0001862793,0.0002359611,0.0001696287,0.01012225,0.000310951,0.0004755165,0.001040374,0.00001522781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856268,0.002317639,0.004389447,0.0008421439,0.00004426281,0.0001649182,0.003944932,0.00007664422,0.002593243],"genre_scores_gemma":[0.9945663,0.000514553,0.003090066,0.0001531156,0.0000399062,0.00006721668,0.00138342,0.000004362723,0.0001810855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007570836,"threshold_uncertainty_score":0.04003888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326041303729645,"score_gpt":0.2924848771518981,"score_spread":0.2692244641146017,"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."}}