{"id":"W4282841736","doi":"10.1177/15357597221096017","title":"Time Is Brain: The Importance of an Accurate <i>SCN1A</i> Prediction Score in the Era of Precision Medicine","year":2022,"lang":"en","type":"letter","venue":"Epiliepsy currents/Epilepsy currents","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Precision medicine; Data science; Medical physics; Computer science; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001064029,0.0006451262,0.0007549986,0.0001688362,0.0002148734,0.00002982116,0.002133759,0.0004919368,0.0007549658],"category_scores_gemma":[0.0003066913,0.0004212008,0.0004097391,0.0004968413,0.00053459,0.00002392564,0.0004805251,0.001716484,0.00001273906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005088365,"about_ca_system_score_gemma":0.0002492814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004669181,"about_ca_topic_score_gemma":0.00001340977,"domain_scores_codex":[0.9950227,0.0007785585,0.001383098,0.001075812,0.001162017,0.0005778823],"domain_scores_gemma":[0.9963852,0.0001856619,0.001176454,0.001928616,0.0002288563,0.00009526265],"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":[0.00023418,0.0004544869,0.01315445,0.0002696891,0.0001345936,0.00002495083,0.0006711243,0.0000821096,0.001302743,0.000003805224,0.9787882,0.004879687],"study_design_scores_gemma":[0.002298553,0.001731194,0.01483082,0.0006621838,0.0002914424,0.00006256341,0.0003378096,0.0004836875,0.0009163819,0.0003297308,0.9773467,0.0007089938],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8959862,0.0110547,0.0000248878,0.08018693,0.003564726,0.002274069,0.006385649,0.00002399616,0.0004988543],"genre_scores_gemma":[0.7104066,0.006843315,0.00004360293,0.2228258,0.008276994,0.0008039679,0.04953883,0.0003396004,0.000921299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1855796,"threshold_uncertainty_score":0.999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973398443582719,"score_gpt":0.2816483017425014,"score_spread":0.2619143173066742,"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."}}