{"id":"W4386843338","doi":"10.1002/epi4.12829","title":"Electroencephalography–functional magnetic resonance imaging for clinical evaluation in focal epilepsy","year":2023,"lang":"en","type":"article","venue":"Epilepsia Open","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Uehara Memorial Foundation","keywords":"Candidacy; Electroencephalography; Epilepsy; Functional magnetic resonance imaging; Magnetic resonance imaging; Concordance; EEG-fMRI; Confidence interval; Medicine; Epilepsy surgery; Psychology; Audiology; Radiology; Internal medicine; Psychiatry","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":[],"consensus_categories":[],"category_scores_codex":[0.003666557,0.000193504,0.0004480692,0.0003532665,0.0001463201,0.00008364347,0.0002798222,0.00008985364,0.0006324848],"category_scores_gemma":[0.0009961959,0.0001710063,0.0002165801,0.0009990509,0.0001416709,0.0002265315,0.0001604686,0.0003249434,0.0003181169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001756346,"about_ca_system_score_gemma":0.0005496852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001136876,"about_ca_topic_score_gemma":0.0001425161,"domain_scores_codex":[0.9970403,0.0003039266,0.0006078796,0.0006913394,0.0006462481,0.0007103545],"domain_scores_gemma":[0.9983219,0.0006492119,0.00007507807,0.0004415816,0.0002609848,0.0002512633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001189711,0.0003171437,0.7309005,0.00001633832,0.0000213966,0.00007367355,0.00003398443,0.000004753859,0.00007241474,0.0004956495,0.04475145,0.222123],"study_design_scores_gemma":[0.008614505,0.001270065,0.9456798,0.0001099404,0.0000662684,0.00002656151,0.00007691802,0.01401906,0.00005005539,0.004549993,0.02538897,0.0001478995],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422954,0.007940055,0.000491444,0.0162669,0.0009154967,0.01280932,0.00009438312,0.0002609633,0.01892606],"genre_scores_gemma":[0.9900532,0.0009934559,0.002134566,0.0007691237,0.0003665198,0.002948059,0.0006368503,0.00004772981,0.002050456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2219751,"threshold_uncertainty_score":0.6973435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096556243831903,"score_gpt":0.4366197264447114,"score_spread":0.3269641020615212,"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."}}