{"id":"W2810795226","doi":"10.1109/tbme.2018.2852755","title":"Sensory Stimulation Training for BCI System Based on Somatosensory Attentional Orientation","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; National Natural Science Foundation of China","keywords":"Brain–computer interface; Somatosensory system; Sensory system; Sensory stimulation therapy; Orientation (vector space); Stimulation; Neuroscience; Neurophysiology; Somatosensory evoked potential; Psychology; Computer science; Electroencephalography; Cognitive psychology","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":[0.0001542952,0.0001686609,0.000146672,0.0003160495,0.0002178476,0.00004247559,0.0001138049,0.0001062916,0.00004923466],"category_scores_gemma":[0.00003934331,0.0001615626,0.0001104724,0.0002587754,0.00009135697,0.000113713,7.456229e-7,0.0001628017,0.00006477154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075032,"about_ca_system_score_gemma":0.00003488737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001367717,"about_ca_topic_score_gemma":5.455398e-7,"domain_scores_codex":[0.998634,0.0000374726,0.0002718511,0.0003842925,0.0003998197,0.000272524],"domain_scores_gemma":[0.9990321,0.0005937297,0.00004941989,0.0001511327,0.00004389702,0.0001296804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001680901,0.0001966086,0.000001080948,0.0001438189,0.00001757289,0.000008947982,0.0003275693,0.3692943,0.6177186,0.0005139927,0.000140531,0.01146887],"study_design_scores_gemma":[0.0006923921,0.000274422,0.00003065867,0.0001458333,0.00001142148,0.00001367352,0.00004681526,0.7595841,0.238122,0.000005439665,0.0009394545,0.0001337248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1479855,9.245157e-7,0.8489817,0.0001605321,0.002141261,0.0002316516,0.00007190507,0.0003448477,0.00008168841],"genre_scores_gemma":[0.9947813,4.122411e-7,0.004433151,0.0002372452,0.0003289844,0.00004988273,0.000007113832,0.00002911051,0.000132761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8467959,"threshold_uncertainty_score":0.658833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04211145513101269,"score_gpt":0.2793944136516739,"score_spread":0.2372829585206612,"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."}}