{"id":"W4289888534","doi":"10.3389/fpsyt.2022.923938","title":"Superior temporal gyrus functional connectivity predicts transcranial direct current stimulation response in Schizophrenia: A machine learning study","year":2022,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Transcranial Magnetic Stimulation Studies","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian VIGOUR Centre; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; The Wellcome Trust DBT India Alliance; Alberta Machine Intelligence Institute; Indian Council of Medical Research; Alberta Innovates; Department of Biotechnology, Ministry of Science and Technology, India; Department of Science and Technology, Ministry of Science and Technology, India; Wellcome Trust","keywords":"Transcranial direct-current stimulation; Resting state fMRI; Superior temporal gyrus; Logistic regression; Medicine; Audiology; Functional magnetic resonance imaging; Psychology; Schizophrenia (object-oriented programming); Physical medicine and rehabilitation; Neuroscience; Stimulation; Psychiatry; Internal medicine","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":[0.001070239,0.0004502475,0.0002673327,0.0004733135,0.0001869823,0.0003574387,0.0002143618,0.0003312998,0.001163044],"category_scores_gemma":[0.003034232,0.000154196,0.0006438789,0.0002443544,0.0002616998,0.0003026316,0.0002364426,0.0004416367,0.000236161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003652803,"about_ca_system_score_gemma":0.0002890123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005984198,"about_ca_topic_score_gemma":0.007041639,"domain_scores_codex":[0.999856,0.00005210809,0.00001309845,0.00003980954,0.00001584792,0.00002308777],"domain_scores_gemma":[0.9990597,0.000573896,0.0001572209,0.00006821251,0.00006847485,0.00007253273],"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":[0.002149046,0.0005764704,0.9072009,0.00008729225,0.0006412439,0.0005055305,0.0003180315,0.02169395,0.008379024,0.000291886,0.000804818,0.05735184],"study_design_scores_gemma":[0.00006255698,0.0006337741,0.7252387,0.00003239733,0.0002283515,0.0003964964,0.0001833222,0.2708767,0.001351096,0.0007042418,0.000266831,0.00002561843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983913,0.0001580304,0.001003162,0.0001043588,0.000006113245,0.00001122234,0.0001501207,0.00001205185,0.0001637073],"genre_scores_gemma":[0.9990895,0.000078434,0.0004717222,0.000009551846,0.000006640707,0.000007968971,0.0002314558,0.000002674918,0.0001020204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005984198,"threshold_uncertainty_score":0.0118987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02446083839546117,"score_gpt":0.2666263807258102,"score_spread":0.242165542330349,"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."}}