{"id":"W2999858333","doi":"10.1038/s41467-019-14166-2","title":"Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Natural Science Foundation of China; National Institute of Child Health and Human Development; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs; U.S. Department of Health and Human Services; National Science Foundation","keywords":"Electrophysiology; Neuroscience; Electroencephalography; Dynamics (music); Biology; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008041495,0.0001098068,0.0001509291,0.00004527179,0.0003371612,0.00002750368,0.0008202418,0.0001713685,0.00003877604],"category_scores_gemma":[0.0014129,0.00009865328,0.0001018827,0.0006771715,0.0002242118,0.00008442047,0.0002480286,0.0009213269,0.00001380505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000464123,"about_ca_system_score_gemma":0.00004152556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002823316,"about_ca_topic_score_gemma":0.00004337366,"domain_scores_codex":[0.9989191,0.0002355453,0.0002505221,0.0002554622,0.0001760574,0.0001632671],"domain_scores_gemma":[0.9981683,0.0009030766,0.0001398462,0.0006216961,0.00009558037,0.00007142761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005182276,0.0001269989,0.0001473108,0.000006802976,0.000009590262,9.097474e-7,0.00002183717,0.001645148,0.5391752,0.4551736,0.002224396,0.001416426],"study_design_scores_gemma":[0.0002656701,0.0003150196,0.007315039,0.00001037502,0.00002608724,0.00001264586,0.00001461169,0.9779242,0.002343476,0.005818594,0.005754668,0.0001995878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4309093,0.001691715,0.09074414,0.4543296,0.001250144,0.001870994,0.0007495849,0.0008788233,0.0175757],"genre_scores_gemma":[0.9923082,0.000202107,0.001237375,0.00577144,0.00006674519,0.00001696763,0.0003139907,0.00001257333,0.00007060036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9762791,"threshold_uncertainty_score":0.4022964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03963506748644536,"score_gpt":0.3114095595566844,"score_spread":0.2717744920702391,"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."}}