{"id":"W2979563119","doi":"10.1155/2019/2503431","title":"A Comparison between BCI Simulation and Neurofeedback for Forward/Backward Navigation in Virtual Reality","year":2019,"lang":"en","type":"article","venue":"Computational Intelligence and Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Brain–computer interface; Neurofeedback; Motor imagery; Computer science; Session (web analytics); Sensorimotor rhythm; Electroencephalography; Context (archaeology); Virtual reality; Support vector machine; Artificial intelligence; Psychology; Neuroscience","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":[0.0005258349,0.0004185211,0.0003197451,0.0004424341,0.00009952643,0.0002944379,0.0002795916,0.0003937212,0.0009577318],"category_scores_gemma":[0.003763162,0.0001230434,0.0002039235,0.0001691339,0.0001932353,0.0003308513,0.0002885379,0.0001666747,0.0001861148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001815288,"about_ca_system_score_gemma":0.0002091711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001282446,"about_ca_topic_score_gemma":0.001526372,"domain_scores_codex":[0.9995759,0.0001746331,0.00003281009,0.0000601612,0.0001177167,0.00003884821],"domain_scores_gemma":[0.998848,0.0007366039,0.00006553235,0.00009559893,0.0001955226,0.00005879661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02058827,0.001906394,0.01200928,0.0009751207,0.0003746194,0.0002467175,0.000873186,0.03249959,0.384642,0.0007354998,0.0009691697,0.5441802],"study_design_scores_gemma":[0.001500738,0.05038212,0.3624846,0.0002199425,0.001198264,0.002870864,0.0007881636,0.4205402,0.1508896,0.001429913,0.007442649,0.0002527878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636129,0.0006624263,0.03307647,0.0001026605,0.00006495242,0.00009345099,0.0000954585,0.0003154269,0.001976212],"genre_scores_gemma":[0.9927447,0.0001926235,0.006528596,0.00003184124,0.00001275529,0.00004692005,0.00007708178,0.00001275088,0.0003528407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001282446,"threshold_uncertainty_score":0.003203928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1333234217647313,"score_gpt":0.4002020913099072,"score_spread":0.266878669545176,"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."}}