{"id":"W3208480795","doi":"10.1016/j.bpsc.2021.10.017","title":"Electroencephalographic Connectivity: A Fundamental Guide and Checklist for Optimal Study Design and Evaluation","year":2021,"lang":"en","type":"review","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC; Canadian Institutes of Health Research; MagVenture; BrainsWay; Vancouver Coastal Health Research Institute; National Health and Medical Research Council; Fondation Brain Canada","keywords":"Computer science; Electroencephalography; Artifact (error); Preprocessor; Standardization; Checklist; Robustness (evolution); Data mining; Artificial intelligence; Psychology; Cognitive psychology; Neuroscience","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":[0.0638103,0.003362826,0.006933534,0.006218095,0.001369768,0.004295326,0.00518305,0.00379218,0.00603739],"category_scores_gemma":[0.1077823,0.001527105,0.002056791,0.003864894,0.005024942,0.003683489,0.002659157,0.00709182,0.004287182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002361669,"about_ca_system_score_gemma":0.01151396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003258066,"about_ca_topic_score_gemma":0.007139101,"domain_scores_codex":[0.9735888,0.01357566,0.008142062,0.001075473,0.003427449,0.0001906263],"domain_scores_gemma":[0.9071651,0.07119402,0.004104063,0.003266144,0.01333267,0.0009379514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005571901,0.0001576331,0.002441683,0.02736451,0.000691979,0.0007052695,0.0004662669,0.001274186,0.002069178,0.03238921,0.1540735,0.7778094],"study_design_scores_gemma":[0.00126683,0.001432033,0.01483469,0.100872,0.00319359,0.007877624,0.001366014,0.005707335,0.005102812,0.2038265,0.6539094,0.0006110642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001605984,0.4002232,0.5152419,0.04391035,0.004840928,0.01694405,0.005958715,0.001505141,0.009769785],"genre_scores_gemma":[0.009043894,0.1987031,0.7406893,0.01069921,0.004613131,0.02908534,0.003068515,0.0004807366,0.003616854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0638103,"threshold_uncertainty_score":0.3374652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.207060546711829,"score_gpt":0.4115810903842397,"score_spread":0.2045205436724107,"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."}}