{"id":"W4317790307","doi":"10.1101/2023.01.23.525101","title":"Neurophysiological signatures of cortical micro-architecture","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of General Medical Sciences; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; National Institutes of Health; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; McGill University; Michael J. Fox Foundation for Parkinson's Research","keywords":"Neurophysiology; Magnetoencephalography; Neuroscience; Computer science; Cortex (anatomy); Electroencephalography; Biology","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":[0.0001484143,0.0001739489,0.0001500141,0.0006938365,0.0001156236,0.0004708136,0.0001345751,0.000230987,0.001622022],"category_scores_gemma":[0.0008973078,0.0001397595,0.00016322,0.0004952727,0.0003024505,0.0003770789,0.0003071577,0.0002089162,0.0002385785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001275653,"about_ca_system_score_gemma":0.0001250956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007407629,"about_ca_topic_score_gemma":0.001500491,"domain_scores_codex":[0.9999391,0.000009556741,0.000004143007,0.00002358676,0.00001329013,0.00001033028],"domain_scores_gemma":[0.999809,0.00005833423,0.00005157851,0.00003008946,0.0000265723,0.00002443009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003317114,0.00005823073,0.08518779,0.000275981,0.0002239895,0.000367288,0.0007052147,0.01322843,0.7494401,0.00395098,0.001939425,0.1442907],"study_design_scores_gemma":[0.000007667709,0.00006929811,0.9467361,0.00001652678,0.00003448082,0.0008357111,0.0002289778,0.02171247,0.02251208,0.006334481,0.001484812,0.00002749106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408891,0.000553914,0.05373348,0.0001888061,0.00001760636,0.00002350123,0.001059452,0.0003162459,0.003217791],"genre_scores_gemma":[0.9903673,0.0002576484,0.008301274,0.0000260886,0.00001327217,0.00001565059,0.0004199448,0.00004511078,0.0005538604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001622022,"threshold_uncertainty_score":0.005426228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02610604816621504,"score_gpt":0.2338928773686813,"score_spread":0.2077868292024663,"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."}}