{"id":"W3097113877","doi":"10.1016/j.nicl.2020.102485","title":"Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Institut universitaire en santé mentale de Montréal; Institut Universitaire en Santé Mentale de Québec; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Engineering and Physical Sciences Research Council; Medical Research Council; Cardiff University; Fonds de Recherche du Québec - Santé; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Magnetoencephalography; Schizophrenia (object-oriented programming); Neuroscience; Psychology; Neuroimaging; Electroencephalography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001748799,0.0001924041,0.0002037955,0.0004066229,0.0001701139,0.0002467612,0.00007201263,0.0001848804,0.001101675],"category_scores_gemma":[0.0009153638,0.00009441371,0.0001201954,0.0001844684,0.0001837462,0.0001563124,0.0002120873,0.0001324202,0.0001251193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294636,"about_ca_system_score_gemma":0.0001125379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001609462,"about_ca_topic_score_gemma":0.002712354,"domain_scores_codex":[0.9999297,0.00001435466,0.00001070536,0.00001941284,0.00001585456,0.00001001966],"domain_scores_gemma":[0.9998361,0.00003958818,0.00006603282,0.00001912472,0.00001527929,0.00002391427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004824654,0.0002463961,0.5807602,0.0001180727,0.0001901135,0.002455029,0.002076533,0.001088552,0.3560464,0.0003321945,0.0006327283,0.05122917],"study_design_scores_gemma":[0.00002499568,0.0003073004,0.9923853,0.000006051856,0.00003644119,0.001640861,0.0002856128,0.001158937,0.003766771,0.0001702309,0.0002076712,0.00000987741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992452,0.00004554777,0.0003898244,0.00001389543,0.000001893301,0.000005532057,0.00009763917,0.000009946835,0.0001906161],"genre_scores_gemma":[0.9995562,0.00002224887,0.0002010917,0.000009271058,0.000002606912,0.000004381276,0.0001224944,0.00000259431,0.00007894247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001609462,"threshold_uncertainty_score":0.003685474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08771843359348735,"score_gpt":0.3343841387657768,"score_spread":0.2466657051722894,"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."}}