{"id":"W7115713270","doi":"10.1162/imag.a.1096","title":"Considering brain state for individualized functional connectivity-based rTMS","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Transcranial Magnetic Stimulation Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"Health Canada; McDonnell Center for Systems Neuroscience; Canadian Institutes of Health Research; Djavad Mowafaghian Centre for Brain Health; Weston Brain Institute; Azrieli Foundation; Sick Kids Foundation; Hospital for Sick Children; Michael Smith Health Research BC; BC Children's Hospital; National Institutes of Health; Vancouver Coastal Health Research Institute; Government of Canada; Fondation Brain Canada","keywords":"Transcranial magnetic stimulation; Functional magnetic resonance imaging; Brain stimulation; Task (project management); Reliability (semiconductor); Brain activity and meditation; Deep brain stimulation; State (computer science)","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":[0.0003519411,0.0001967552,0.0002074759,0.0002826604,0.000671675,0.0002218897,0.0002839252,0.00001831564,0.00001354327],"category_scores_gemma":[0.007246671,0.0002017947,0.00008745664,0.0008397226,0.0006588318,0.0002700681,0.00008348635,0.0001323241,0.000007745315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003427609,"about_ca_system_score_gemma":0.0001990113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001179819,"about_ca_topic_score_gemma":0.000004300852,"domain_scores_codex":[0.9979602,0.0001330778,0.0002863844,0.0007978407,0.0003778461,0.0004446902],"domain_scores_gemma":[0.99606,0.003406759,0.0001207182,0.0002580224,0.00008511328,0.00006936953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008459736,0.00006145552,0.004975551,0.00002913155,9.774919e-7,0.000008704298,0.00008148835,0.005531027,0.9800367,0.003401103,0.001619309,0.004169936],"study_design_scores_gemma":[0.009133468,0.0001829891,0.2431753,0.0001200854,0.00004451142,0.00003283241,0.00004903605,0.2392927,0.3782268,0.01482657,0.1140676,0.0008482067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2897413,0.00004536206,0.6865764,0.01743434,0.002577302,0.0009248094,0.0001106647,0.0007087791,0.001881057],"genre_scores_gemma":[0.9765685,0.0000018104,0.001315242,0.02155266,0.00002204858,0.0001007844,8.584802e-7,0.0000157279,0.0004224214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6868271,"threshold_uncertainty_score":0.8675466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05993554619527252,"score_gpt":0.327311967404261,"score_spread":0.2673764212089885,"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."}}