{"id":"W2977916355","doi":"10.1038/s41598-019-50750-8","title":"Topography and behavioral relevance of the global signal in the human brain","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; RWTH Aachen University; National Research Foundation Singapore; Deutsche Forschungsgemeinschaft; National Research Foundation; National Institute of Mental Health; Canadian Institute for Advanced Research; U.S. Department of Health and Human Services","keywords":"Neuroimaging; Relevance (law); Artifact (error); SIGNAL (programming language); Functional neuroimaging; Trait; Principal component analysis; Cognition; Computer science; Cognitive psychology; Neuroscience; Psychology; Functional connectivity; Artificial intelligence; Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.001241682,0.00008168223,0.0001065198,0.00005028649,0.0003018228,0.00009142207,0.000216291,0.00002534287,0.00002305079],"category_scores_gemma":[0.001035818,0.00004833332,0.00007003236,0.0008834784,0.000665778,0.0001298667,0.0001459032,0.0001057738,0.000002967747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000235945,"about_ca_system_score_gemma":0.00003807658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000055496,"about_ca_topic_score_gemma":0.0001768162,"domain_scores_codex":[0.9983239,0.0001499397,0.0002401421,0.0005451397,0.0005710169,0.000169869],"domain_scores_gemma":[0.9985645,0.0006111339,0.0001740441,0.0005939668,0.00003812789,0.00001821119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005649331,0.0001269278,0.6838163,0.00001437141,0.000002100942,0.00004935303,0.0006581183,0.00003268035,0.2995957,0.004086926,0.01114671,0.0004650972],"study_design_scores_gemma":[0.0002828595,0.0001377438,0.8153686,0.00006344741,0.00001290466,0.000400231,0.0005526881,0.00003668186,0.06210656,0.08161476,0.03919516,0.0002283686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922031,0.00004306585,0.000002164767,0.002722088,0.002058092,0.0003331781,0.000004081345,0.00001209752,0.002622154],"genre_scores_gemma":[0.9987985,4.447593e-7,0.00001122877,0.0004843795,0.00001632603,0.00001040798,4.826216e-7,0.000003084009,0.0006751178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2374892,"threshold_uncertainty_score":0.2453087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03165115466142557,"score_gpt":0.2939829765237962,"score_spread":0.2623318218623706,"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."}}