{"id":"W4224238561","doi":"10.3389/fnhum.2022.881922","title":"Editorial: Cognitive and Motor Control Based on Brain-Computer Interfaces for Improving the Health and Well-Being in Older Age","year":2022,"lang":"en","type":"editorial","venue":"Frontiers in Human Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Hum; Brain–computer interface; Cognition; Motor control; Control (management); Neuroscience; Psychology; Human–computer interaction; Cognitive science; Physical medicine and rehabilitation; Computer science; Medicine; Artificial intelligence; Electroencephalography; History","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":[0.004826699,0.004086983,0.004063141,0.003208827,0.002745326,0.005377572,0.002956351,0.01594069,0.02722688],"category_scores_gemma":[0.01851838,0.0008836123,0.00245088,0.001053612,0.001714069,0.003176993,0.001440336,0.0145111,0.01914834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001947505,"about_ca_system_score_gemma":0.002296801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001385367,"about_ca_topic_score_gemma":0.00374592,"domain_scores_codex":[0.9973936,0.0004230774,0.0003670509,0.0003865909,0.001224693,0.0002050523],"domain_scores_gemma":[0.9860416,0.005618517,0.0007833455,0.0002838401,0.005263644,0.002009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004983148,0.00000923376,0.0000122477,0.0001826775,0.00001243623,0.00007947464,0.000005218802,0.00001660988,0.00004141032,0.0001424049,0.9955009,0.003947544],"study_design_scores_gemma":[0.0001359003,0.00004943023,0.0002914711,0.0006355428,0.00007260398,0.0003983263,0.00003196987,0.0002024904,0.0001705882,0.001256123,0.9967306,0.00002505573],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002624004,0.003462855,0.0001402793,0.02131225,0.9734422,0.00002929243,0.00009507517,0.00005698434,0.00143488],"genre_scores_gemma":[0.0003418055,0.003061202,0.00009229794,0.01472313,0.9728741,0.00003580638,0.00004703313,0.00003818435,0.008786523],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02722688,"threshold_uncertainty_score":0.09108293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01099964520631825,"score_gpt":0.2726036414934,"score_spread":0.2616039962870818,"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."}}