{"id":"W4410051974","doi":"10.1111/epi.18446","title":"Development and validation of International Classification of Diseases, 9th and 10th Revision, Clinical Modification‐based algorithms to identify adult epilepsy in electronic health records","year":2025,"lang":"en","type":"article","venue":"Epilepsia","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Center for Advancing Translational Sciences; National Institute on Aging","keywords":"Epilepsy; Diagnosis code; Medicine; Algorithm; Predictive value; Electronic health record; Pediatrics; Internal medicine; Health care; Psychiatry; Mathematics; Population","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":[0.06064539,0.001139436,0.001051422,0.005806489,0.0005681374,0.002438202,0.001717214,0.001239612,0.0007528594],"category_scores_gemma":[0.133453,0.0004353078,0.001639709,0.002469132,0.0005785217,0.002067072,0.001516845,0.00108086,0.0003661786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377315,"about_ca_system_score_gemma":0.003028749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004632569,"about_ca_topic_score_gemma":0.004729994,"domain_scores_codex":[0.9693248,0.01815463,0.005065467,0.002611434,0.00424734,0.0005962273],"domain_scores_gemma":[0.8867068,0.07575592,0.0142111,0.003447545,0.01897704,0.0009015471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005290775,0.0004081748,0.9147532,0.0002677759,0.0009626506,0.00002923525,0.0002905153,0.00699218,0.000188313,0.0006573941,0.002268147,0.0726533],"study_design_scores_gemma":[0.0007346597,0.001196116,0.6363583,0.0010372,0.001142727,0.0004708108,0.0007880921,0.3493018,0.001837405,0.003343843,0.003685838,0.0001032458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8967851,0.005372862,0.08252031,0.00173711,0.0002672647,0.002891377,0.004496729,0.0006731958,0.005255956],"genre_scores_gemma":[0.8615954,0.001071241,0.1314809,0.0003276338,0.0000826808,0.001267921,0.003844961,0.00004312631,0.0002862381],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06064539,"threshold_uncertainty_score":0.3207273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018435686565271,"score_gpt":0.4089142500125934,"score_spread":0.3687298931469407,"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."}}