{"id":"W3200423119","doi":"10.1101/2021.09.09.459695","title":"Local neuronal excitation and global inhibition during epileptic fast ripples in humans","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Health Canada; Government of Canada; Université de Toulouse; Natural Sciences and Engineering Research Council of Canada; European Commission; Fondation Brain Canada","keywords":"Ictal; Local field potential; Neuroscience; Premovement neuronal activity; Biological neural network; Neurology; Homogeneous; Deep brain stimulation; Epilepsy; Computer science; Psychology; Medicine; Physics; Internal medicine","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":[0.0001058816,0.0001490838,0.0001847664,0.0002152661,0.00007966823,0.0002429672,0.00007876965,0.0001795124,0.0008147419],"category_scores_gemma":[0.0005476865,0.00008923311,0.00008925532,0.0001015235,0.0002329658,0.0001415123,0.0001133328,0.0001244249,0.0001344163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007726479,"about_ca_system_score_gemma":0.00005355237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009880159,"about_ca_topic_score_gemma":0.001709878,"domain_scores_codex":[0.9999574,0.000007234215,0.000002313859,0.00001703107,0.000008897057,0.000007078472],"domain_scores_gemma":[0.9999171,0.00002832757,0.00002308161,0.0000137196,0.000008387346,0.000009317651],"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":[0.005295625,0.0002576216,0.257974,0.0003374153,0.0004000658,0.007120872,0.002427738,0.004978828,0.5433511,0.001300522,0.003143238,0.173413],"study_design_scores_gemma":[0.00004197395,0.0004710133,0.9704674,0.00002473558,0.00006724321,0.004185619,0.0004249083,0.005365648,0.01646867,0.0009292682,0.001526312,0.00002717654],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945266,0.0002172504,0.003309546,0.00004643796,0.00000957779,0.00001658918,0.0001847901,0.00005527892,0.001633917],"genre_scores_gemma":[0.9990129,0.0000596482,0.0004983456,0.00001713009,0.000005040327,0.000006064889,0.00008739135,0.000007239116,0.0003063327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009880159,"threshold_uncertainty_score":0.002725542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660500375073972,"score_gpt":0.2314818535743994,"score_spread":0.2148768498236596,"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."}}