{"id":"W4367302217","doi":"10.1016/j.chaos.2023.113453","title":"Spatial permutation entropy distinguishes resting brain states","year":2023,"lang":"en","type":"article","venue":"Chaos Solitons & Fractals","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Financiadora de Estudos e Projetos; Institució Catalana de Recerca i Estudis Avançats; Fundação de Amparo à Pesquisa do Estado de São Paulo; Deutscher Akademischer Austauschdienst","keywords":"Permutation (music); Eyes open; Electroencephalography; Entropy (arrow of time); Raw data; Transfer entropy; Computer science; Instant; Pattern recognition (psychology); Artificial intelligence; Principle of maximum entropy; Mathematics; Statistics; Psychology; Neuroscience","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007385598,0.0002941046,0.0003295329,0.001832447,0.0001930222,0.0007350025,0.0001571814,0.00023923,0.001476034],"category_scores_gemma":[0.004628945,0.000107386,0.0003909382,0.0008183682,0.0005154015,0.0006346161,0.0004608136,0.0002288049,0.0001835499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001438962,"about_ca_system_score_gemma":0.000150549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004742843,"about_ca_topic_score_gemma":0.0005089983,"domain_scores_codex":[0.9996573,0.0001136545,0.0000403727,0.00006050311,0.00007653483,0.00005168427],"domain_scores_gemma":[0.9979506,0.001301911,0.0002863737,0.0001941651,0.0001772718,0.00008977756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004797916,0.0004900924,0.3546637,0.0004392142,0.0008045463,0.001180805,0.001634587,0.05196866,0.1534905,0.0115234,0.001797013,0.4172096],"study_design_scores_gemma":[0.00003849937,0.0008357536,0.7730472,0.00002770716,0.000129363,0.0008732409,0.0003933939,0.1918335,0.01328754,0.01858701,0.0008080264,0.0001388519],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621683,0.0001400247,0.03522548,0.00006484368,0.00001522841,0.00003116133,0.0004616824,0.0001028581,0.00179032],"genre_scores_gemma":[0.9967975,0.00002252787,0.002835184,0.00000433903,0.000008057968,0.00001076831,0.0002065416,0.000006834081,0.0001082963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001832447,"threshold_uncertainty_score":0.004937768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03773540691760772,"score_gpt":0.3131362302090342,"score_spread":0.2754008232914265,"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."}}