{"id":"W3126696394","doi":"10.1177/1535759721991161","title":"Emerging Trends in Neuroimaging of Epilepsy","year":2021,"lang":"en","type":"article","venue":"Epiliepsy currents/Epilepsy currents","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Canada First Research Excellence Fund; Institute of Neurosciences, Mental Health and Addiction; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Prognostics; Medicine; Epilepsy; Brain function; Magnetic resonance imaging; Neuroscience; Artificial intelligence; Computer science; Psychiatry; Psychology; Radiology; Data mining","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":[0.0002795933,0.0004995171,0.0009256483,0.0008270714,0.0001273607,0.0000318404,0.0003919975,0.0001211359,0.0006526402],"category_scores_gemma":[0.0002570403,0.0005417722,0.0004048336,0.002417102,0.0002005906,0.0003047732,0.0003204597,0.0009348946,0.00005903599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001344765,"about_ca_system_score_gemma":0.0001404382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002347014,"about_ca_topic_score_gemma":0.000006006649,"domain_scores_codex":[0.9960054,0.0001490457,0.001223547,0.001138468,0.0006742388,0.0008093108],"domain_scores_gemma":[0.997624,0.0001115814,0.0003718117,0.001279891,0.0002965011,0.0003161594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008504103,0.001861552,0.6868519,0.0002284664,0.00003916378,0.0001460779,0.0002388926,0.0000625901,0.008654078,0.001199639,0.0055318,0.2951008],"study_design_scores_gemma":[0.007640884,0.0003540748,0.8013484,0.002260895,0.000334991,0.0004875739,0.0003160225,0.007931049,0.03140453,0.003237109,0.1432155,0.001468876],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681048,0.003488484,0.008308971,0.003824295,0.002152626,0.00091415,0.000226406,0.0006619754,0.01231826],"genre_scores_gemma":[0.9916413,0.0008819242,0.005642354,0.0003309327,0.0002079127,0.0001193148,0.0004439424,0.0001034621,0.0006288438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2936319,"threshold_uncertainty_score":0.9997034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07205264821945591,"score_gpt":0.3910501762932826,"score_spread":0.3189975280738267,"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."}}