{"id":"W2922157655","doi":"10.1016/j.eplepsyres.2019.02.006","title":"Effective connectivity analysis of iEEG and accurate localization of the epileptogenic focus at the onset of operculo-insular seizures","year":2019,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Institut de Valorisation des Données; Epilepsy Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Insular cortex; Epilepsy; Statistical parametric mapping; Electroencephalography; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001711115,0.0002946322,0.000152582,0.001055538,0.0001629683,0.0003487809,0.0001584743,0.0002751359,0.001158095],"category_scores_gemma":[0.001156589,0.00009184313,0.0001529906,0.0004662824,0.0001589102,0.0004353753,0.0001647379,0.0001878105,0.0001541841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001320522,"about_ca_system_score_gemma":0.0001639236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001998918,"about_ca_topic_score_gemma":0.005319101,"domain_scores_codex":[0.9999267,0.00001949252,0.000005206799,0.00001528473,0.00001594156,0.00001726021],"domain_scores_gemma":[0.9998521,0.00006908752,0.00002470972,0.000009121774,0.00003206452,0.00001296574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001593828,0.0001367472,0.05595119,0.0004134519,0.0002651136,0.003027304,0.0004160902,0.01765419,0.612413,0.005602218,0.003786383,0.2987404],"study_design_scores_gemma":[0.00006505409,0.000366533,0.6779526,0.00008226431,0.000259538,0.00650683,0.0005424272,0.19287,0.1088345,0.007898812,0.004556548,0.00006482322],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8676222,0.001601651,0.1244465,0.0002932643,0.00007593024,0.00006087188,0.001099604,0.000335034,0.004464961],"genre_scores_gemma":[0.9886092,0.0002863949,0.01010461,0.00001995487,0.00003601093,0.00001620374,0.0003542452,0.00003352319,0.0005398685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001998918,"threshold_uncertainty_score":0.003974557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03965681422772353,"score_gpt":0.3468990095088597,"score_spread":0.3072421952811362,"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."}}