{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003550622,0.0002342382,0.0003805141,0.00009642783,0.0001019395,0.00009626293,0.0002643038,0.0001535044,0.00003827704],"category_scores_gemma":[0.006352478,0.0002260613,0.0001861932,0.0006053892,0.000180614,0.0003962372,0.0002591814,0.000957431,0.0001220023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005966614,"about_ca_system_score_gemma":0.00005644266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002776717,"about_ca_topic_score_gemma":0.00007761592,"domain_scores_codex":[0.9966528,0.0007324885,0.0008674258,0.001074992,0.0003358028,0.0003364315],"domain_scores_gemma":[0.9982042,0.0009045625,0.0002693218,0.0003453743,0.00004090738,0.0002356681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005915268,0.001769573,0.4974078,0.0001624146,0.00001784902,0.001784698,0.0004929565,0.0008895429,0.1866563,0.006202373,0.004949808,0.2937514],"study_design_scores_gemma":[0.004066565,0.0031076,0.2894517,0.00005868545,0.00002492442,0.00007139437,0.00005567487,0.6930548,0.0039093,0.001840658,0.003533438,0.0008252484],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904751,0.000003945063,0.0007958032,0.005592172,0.001227385,0.0003832884,0.0000476449,0.0001799681,0.001294673],"genre_scores_gemma":[0.9918179,0.00001603366,0.0002380167,0.007572177,0.000245562,0.000008117489,0.00001786941,0.0000370453,0.00004729867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6921653,"threshold_uncertainty_score":0.921851,"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."}}