{"id":"W2972141338","doi":"10.1016/j.neuroscience.2019.08.016","title":"Clinical Application of Targeted Next-Generation Sequencing Panels and Whole Exome Sequencing in Childhood Epilepsy","year":2019,"lang":"en","type":"article","venue":"Neuroscience","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Epilepsy; Exome sequencing; Medicine; Genetic testing; Medical diagnosis; Exome; Epilepsy syndromes; Medical genetics; Disease; Pediatrics; Ketogenic diet; Bioinformatics; Genetics; Psychiatry; Internal medicine; Pathology; Biology; Mutation; Gene","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":[0.0007924976,0.0004290798,0.0003330374,0.0005650047,0.0002308245,0.000692985,0.0002498371,0.0005904278,0.001686267],"category_scores_gemma":[0.002098061,0.0001309532,0.0002595816,0.0004057161,0.000223358,0.0004607552,0.0004467138,0.0003981565,0.0003977417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000302985,"about_ca_system_score_gemma":0.0004336925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001526248,"about_ca_topic_score_gemma":0.003103992,"domain_scores_codex":[0.9996938,0.0001100028,0.00002968299,0.00007625617,0.00006277089,0.00002750697],"domain_scores_gemma":[0.999461,0.0003043798,0.00005202758,0.0000318155,0.0001080988,0.00004263548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002067967,0.0001825,0.3322096,0.0004866297,0.0004441746,0.01639024,0.0005244043,0.009200634,0.1360746,0.003834557,0.01582539,0.4827592],"study_design_scores_gemma":[0.0002389447,0.001369265,0.7164268,0.0008425335,0.0007994623,0.05874734,0.001091291,0.04462293,0.09240507,0.01923685,0.06409114,0.0001284017],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8950189,0.02171862,0.04197683,0.006559222,0.0004521135,0.0001600846,0.003404152,0.0006350972,0.03007504],"genre_scores_gemma":[0.9782547,0.004404617,0.01390318,0.001190271,0.00009584271,0.00004815336,0.0006122186,0.00005372788,0.001437303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001686267,"threshold_uncertainty_score":0.005641162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04013280990904679,"score_gpt":0.2793621237403262,"score_spread":0.2392293138312794,"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."}}