{"id":"W2619484096","doi":"10.1161/strokeaha.116.016304","title":"Contralesional Brain–Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":238,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Neurorehabilitation; Physical medicine and rehabilitation; Exoskeleton; Medicine; Brain–computer interface; Stroke (engine); Rehabilitation; Powered exoskeleton; Chronic stroke; Physical therapy; Electroencephalography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001798276,0.0002968337,0.0002311908,0.0002454303,0.0001792216,0.0001445216,0.0001418262,0.0001674249,0.001945146],"category_scores_gemma":[0.0005390879,0.00005259246,0.0001538277,0.0001054187,0.0001764375,0.00009357959,0.0001906795,0.0001080841,0.0001554951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000102663,"about_ca_system_score_gemma":0.0002533867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007651147,"about_ca_topic_score_gemma":0.002019947,"domain_scores_codex":[0.9999197,0.00002390378,0.00000952958,0.00001222454,0.0000180874,0.00001655616],"domain_scores_gemma":[0.9999236,0.00002119653,0.00001772227,0.00000620349,0.00001571149,0.00001546757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01305034,0.0102154,0.1450272,0.0007416026,0.0003201431,0.00248126,0.001595471,0.004525356,0.2545455,0.0002233289,0.002412994,0.5648615],"study_design_scores_gemma":[0.002120024,0.06653495,0.8668073,0.0001129863,0.0003548095,0.003205186,0.001013571,0.01661674,0.03954211,0.0004734927,0.00316335,0.00005538684],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988114,0.00006973863,0.0006502566,0.00001791701,0.000004058772,0.00004460361,0.00001989808,0.00001792639,0.0003643071],"genre_scores_gemma":[0.9991758,0.00005022609,0.000416874,0.00001881604,0.000004430381,0.0000820061,0.00004516256,0.000001359089,0.0002052738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001945146,"threshold_uncertainty_score":0.006507158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293247540716804,"score_gpt":0.2907395258839088,"score_spread":0.2678070504767407,"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."}}