{"id":"W4287996245","doi":"10.48550/arxiv.1912.04828","title":"Navigating in Virtual Reality using Thought: The Development and\\n Assessment of a Motor Imagery based Brain-Computer Interface","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"","keywords":"Brain–computer interface; Motor imagery; Neurofeedback; Virtual reality; Computer science; Electroencephalography; Pipeline (software); Interface (matter); Human–computer interaction; Perspective (graphical); Psychology; Artificial intelligence; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006251396,0.0003259988,0.0001272152,0.0003652734,0.0001300994,0.0008292079,0.0004798259,0.0003546036,0.001463037],"category_scores_gemma":[0.001748211,0.000126852,0.0002219564,0.000154267,0.0007906522,0.0006454665,0.0005923276,0.0002865026,0.0002041817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002746848,"about_ca_system_score_gemma":0.0004816922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000953986,"about_ca_topic_score_gemma":0.001912631,"domain_scores_codex":[0.999621,0.0001556894,0.00002358204,0.00007671949,0.0000973389,0.00002557693],"domain_scores_gemma":[0.999692,0.0001399391,0.00005581677,0.00003454984,0.00003940943,0.00003834219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007733554,0.0006243543,0.01437976,0.0006259539,0.00006800301,0.0004018472,0.001848481,0.001985969,0.3451616,0.00593439,0.001432538,0.6267637],"study_design_scores_gemma":[0.0008774246,0.01341782,0.3083867,0.0006286885,0.0005955228,0.01437757,0.003421987,0.148219,0.4309545,0.02181645,0.05675977,0.0005446411],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7627448,0.001895278,0.2241769,0.0008158004,0.0001337662,0.0004041462,0.0001263138,0.0007801468,0.008922791],"genre_scores_gemma":[0.8698149,0.0008035068,0.1272157,0.0002083726,0.0000335496,0.0001298475,0.00006342882,0.0000299808,0.001700652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001463037,"threshold_uncertainty_score":0.004894316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099117347977391,"score_gpt":0.2801929793737843,"score_spread":0.1702812445760453,"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."}}