{"id":"W2767709153","doi":"10.1016/j.jns.2017.11.007","title":"Neural coupling between contralesional motor and frontoparietal networks correlates with motor ability in individuals with chronic stroke","year":2017,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario; Baycrest Hospital; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Heart and Stroke Foundation; University of Toronto","funders":"","keywords":"Supplementary motor area; Neuroscience; Motor cortex; Primary motor cortex; Functional magnetic resonance imaging; Physical medicine and rehabilitation; Psychology; Premotor cortex; Dorsolateral prefrontal cortex; Transcranial magnetic stimulation; Stroke (engine); Motor area; Prefrontal cortex; Medicine; Cognition; Dorsum; Anatomy; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00119529,0.0001716512,0.0003488761,0.00005252277,0.001221451,0.0002835464,0.0009484175,0.0000701566,0.000009653763],"category_scores_gemma":[0.004703253,0.0000766637,0.00007510919,0.0001235798,0.002776772,0.000593106,0.000325405,0.0006901056,4.395017e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003536821,"about_ca_system_score_gemma":0.0001003394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001677432,"about_ca_topic_score_gemma":0.00005885015,"domain_scores_codex":[0.9979996,0.0001928174,0.0003067776,0.0004056024,0.0007387006,0.0003564901],"domain_scores_gemma":[0.9941895,0.004846661,0.0006108513,0.0001951589,0.0000531688,0.0001046489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002120277,0.00004111466,0.98118,0.000002621437,0.000007909579,0.00002339537,0.00001790373,0.01591175,0.002215116,0.00007165374,0.00001356984,0.000302964],"study_design_scores_gemma":[0.0007273401,0.002804612,0.9717276,0.00002876022,0.00002189821,0.000137077,0.00001034334,0.02375751,0.0002656225,0.0003784052,0.0000396663,0.0001011757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890352,0.00016098,0.00006071229,0.01010086,0.0003441863,0.0002328668,0.00001085321,0.000008996937,0.00004527102],"genre_scores_gemma":[0.9990913,0.00002587787,0.00009906698,0.0005389176,0.0002188094,0.000004775523,3.501774e-8,0.000004679395,0.0000165089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01005606,"threshold_uncertainty_score":0.9999371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04095365290490575,"score_gpt":0.2713338583620135,"score_spread":0.2303802054571077,"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."}}