{"id":"W2042695103","doi":"10.1016/j.actaastro.2008.09.008","title":"Prospects of brain–machine interfaces for space system control","year":2008,"lang":"en","type":"article","venue":"Acta Astronautica","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Brain–computer interface; Computer science; Human–computer interaction; Space (punctuation); Measure (data warehouse); Control system; Control (management); Control engineering; Human–machine system; Artificial intelligence; Systems engineering; Engineering; Electrical engineering; Neuroscience; Data mining; Operating system; Electroencephalography","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":[0.002080966,0.0008189189,0.0009184408,0.0007860977,0.0004736809,0.002208343,0.001573727,0.004350069,0.01538941],"category_scores_gemma":[0.002656703,0.0002696534,0.0004872272,0.0007547152,0.001755939,0.004387679,0.00092203,0.002015006,0.003216645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005969231,"about_ca_system_score_gemma":0.001138434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000765908,"about_ca_topic_score_gemma":0.0006059071,"domain_scores_codex":[0.9995864,0.0001553785,0.00002089629,0.00007193154,0.0001051612,0.00006026077],"domain_scores_gemma":[0.9983678,0.001072696,0.00007035824,0.00007786634,0.0002876161,0.0001235676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001152263,0.0005839988,0.002345206,0.001501254,0.0001281092,0.0003862314,0.0002839011,0.0181538,0.01273812,0.4554999,0.04958987,0.4576373],"study_design_scores_gemma":[0.0001943507,0.001088815,0.003025699,0.0007878817,0.00007721311,0.0004721989,0.0005197216,0.0660825,0.004551049,0.6630769,0.2600078,0.0001157463],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02469215,0.4410233,0.3333853,0.05859069,0.0052672,0.0001200395,0.0004210206,0.001036945,0.1354634],"genre_scores_gemma":[0.5452499,0.2334501,0.1477703,0.009941519,0.01527031,0.0004909087,0.0009376206,0.0001782046,0.04671117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01538941,"threshold_uncertainty_score":0.05148274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200596709114649,"score_gpt":0.2537894739674142,"score_spread":0.2337298030559493,"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."}}