{"id":"W2160307384","doi":"10.1098/rstb.2013.0528","title":"Mapping human brain networks with cortico-cortical evoked potentials","year":2014,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":246,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Nemzeti Kutatási és Technológiai Hivatal; Hungarian Scientific Research Fund; Epilepsy Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Neuroscience; Computer science; Neuroimaging; Cognition; Sensory system; Human brain; Cerebral cortex; Cortex (anatomy); Psychology","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":[0.0002903548,0.0004224549,0.0001871948,0.0006795378,0.0001292069,0.0005685878,0.0002507099,0.0004259002,0.001558239],"category_scores_gemma":[0.002078763,0.0001429104,0.0002175058,0.0009249529,0.0003482586,0.000663366,0.0003712251,0.0002836948,0.0003047551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618355,"about_ca_system_score_gemma":0.0001807564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001114659,"about_ca_topic_score_gemma":0.001373788,"domain_scores_codex":[0.9998084,0.00007075085,0.00001039602,0.00004741537,0.00004677479,0.00001638777],"domain_scores_gemma":[0.9998153,0.0001059324,0.00003077097,0.00001489002,0.00002420303,0.000008934929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007483118,0.0001483798,0.02623742,0.003057236,0.0005696348,0.002438269,0.001017357,0.03375695,0.3678427,0.01816588,0.007567231,0.5384507],"study_design_scores_gemma":[0.0002806764,0.001015357,0.4772931,0.0006012007,0.0006119678,0.01548993,0.001216767,0.1911044,0.1533005,0.116851,0.04197419,0.0002609317],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3751249,0.01540436,0.5841688,0.0008861928,0.0001368275,0.000762784,0.003497721,0.0009017859,0.01911655],"genre_scores_gemma":[0.8904356,0.009454221,0.096782,0.0002281318,0.0001225406,0.0004803702,0.0007988944,0.00008486091,0.001613499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001558239,"threshold_uncertainty_score":0.005212843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06843966787218653,"score_gpt":0.2772133590771655,"score_spread":0.208773691204979,"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."}}