{"id":"W3217552032","doi":"10.1101/2021.11.09.467906","title":"Altered brain criticality in Schizophrenia: New insights from MEG","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Engineering and Physical Sciences Research Council; Medical Research Council; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Cardiff University","keywords":"Magnetoencephalography; Schizophrenia (object-oriented programming); Similarity (geometry); Psychology; Neuroscience; Population; Resting state fMRI; Psychosis; Brain activity and meditation; Cognitive psychology; Artificial intelligence; Electroencephalography; Medicine; Computer science; Psychiatry","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004726191,0.000609002,0.001723623,0.0005611699,0.0001233987,0.0006674221,0.0007363753,0.0006352412,0.001033678],"category_scores_gemma":[0.0005415794,0.0007867403,0.0004497919,0.0009165646,0.0000838206,0.0002898253,0.0007780895,0.0009153973,0.0003017936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004236681,"about_ca_system_score_gemma":0.0003893986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01299005,"about_ca_topic_score_gemma":0.0006190558,"domain_scores_codex":[0.9957086,0.0001226057,0.001648479,0.001805219,0.0001357821,0.0005792627],"domain_scores_gemma":[0.9966325,0.0001367897,0.0006369487,0.00201678,0.0001711955,0.0004057783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004794685,0.002667948,0.2264936,0.002652548,0.006203719,0.00137006,0.0007197583,0.001407768,0.1163229,0.629447,0.01219302,0.00004215391],"study_design_scores_gemma":[0.003206176,0.0000641754,0.9208055,0.001044322,0.0001561221,2.534908e-8,0.00003594626,0.007769689,0.006724024,0.002185344,0.05467942,0.003329291],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746974,0.01553375,0.005064424,0.001309175,0.001847109,0.0004442885,0.0007991813,0.0001722725,0.0001323818],"genre_scores_gemma":[0.9938578,0.0002075511,0.004320396,0.0003805848,0.001021598,0.00006908589,0.000003627242,0.000110789,0.00002856027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6943119,"threshold_uncertainty_score":0.9998795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02535209158750614,"score_gpt":0.2095095667054702,"score_spread":0.1841574751179641,"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."}}