{"id":"W2049338671","doi":"10.1111/epi.12895","title":"<scp>ICD</scp> coding for epilepsy: Past, present, and future—A report by the International League Against Epilepsy Task Force on <scp>ICD</scp> codes in epilepsy","year":2015,"lang":"en","type":"article","venue":"Epilepsia","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"UCB Pharma; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research; National Institutes of Health; Ministero della Salute; European Commission; Alberta Health Services; Centers for Disease Control and Prevention; Epilepsy Foundation; U.S. Department of Defense","keywords":"Epilepsy; League; Coding (social sciences); Neuroscience; Medicine; Psychology; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.001074588,0.0005605794,0.0005117923,0.0001546614,0.0002786623,0.0002112779,0.0007975091,0.0004009553,0.000005770047],"category_scores_gemma":[0.0008324612,0.0004655441,0.0002960255,0.000183704,0.0002500679,0.0000331408,0.0003873098,0.0003490596,0.00002011236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001012404,"about_ca_system_score_gemma":0.0002412569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005532148,"about_ca_topic_score_gemma":0.00004758567,"domain_scores_codex":[0.9965748,0.0001709696,0.0008121126,0.001147508,0.0004755943,0.0008190027],"domain_scores_gemma":[0.9975022,0.0004103999,0.000481856,0.0008724435,0.0002949737,0.0004381457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001527522,0.0004604683,0.0707738,0.00007381382,0.0003579202,0.0001776603,0.0006906105,0.0005208643,0.03627334,0.001660419,0.8848835,0.003974815],"study_design_scores_gemma":[0.002502315,0.0005115884,0.02025049,0.00006566161,0.0000737843,0.0001891104,0.002797985,0.001146116,0.01405731,0.0009740493,0.9571912,0.0002403647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976643,0.003017854,0.001159423,0.002139668,0.001794523,0.001278696,0.001018812,0.00005784991,0.01289017],"genre_scores_gemma":[0.9817438,0.001154766,0.0004978151,0.001370574,0.004483293,0.0003851824,0.002726934,0.0001226471,0.007515036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07230769,"threshold_uncertainty_score":0.9997796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01390995055107767,"score_gpt":0.2569021720650622,"score_spread":0.2429922215139845,"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."}}