{"id":"W1989843096","doi":"10.3389/fnins.2014.00302","title":"Does EMG control lead to distinct motor adaptation?","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Defense Science and Engineering Graduate; U.S. Department of Defense; National Science Foundation","keywords":"Adaptation (eye); Computer science; Interface (matter); Motor control; Control (management); Bayesian probability; Brain–computer interface; Task (project management); Human–computer interaction; Artificial intelligence; Psychology; Engineering; Electroencephalography; 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":[0.001332568,0.0003517854,0.0005485294,0.0003302701,0.0001385006,0.0007231771,0.0003676039,0.0008131756,0.001491983],"category_scores_gemma":[0.01174078,0.0003837951,0.0006428864,0.0002209686,0.0007650677,0.001145056,0.0005121756,0.0005391249,0.0002042327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002612446,"about_ca_system_score_gemma":0.0001994444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007574478,"about_ca_topic_score_gemma":0.0005634454,"domain_scores_codex":[0.9992933,0.0001699529,0.00006472468,0.0002213674,0.0001693118,0.0000813595],"domain_scores_gemma":[0.9974757,0.001540717,0.0002546125,0.0004305165,0.0001837909,0.0001146671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003028477,0.0005937025,0.04427195,0.0006804506,0.0005805814,0.000709317,0.001089521,0.02576083,0.7415776,0.008436838,0.0005220623,0.1727488],"study_design_scores_gemma":[0.0002184234,0.003080704,0.6550693,0.0001799015,0.0003575218,0.002062364,0.0006202984,0.1893379,0.1097244,0.03628816,0.002850821,0.0002102085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9345009,0.001517178,0.05936241,0.0004399125,0.00008956682,0.00008279225,0.0001455708,0.0002815056,0.003580255],"genre_scores_gemma":[0.9968754,0.000275587,0.002301678,0.0000960416,0.00001475432,0.00002371492,0.00004814123,0.00002728904,0.0003375315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001491983,"threshold_uncertainty_score":0.007047355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007640073390003272,"score_gpt":0.2019716102697147,"score_spread":0.1943315368797114,"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."}}