{"id":"W2601067397","doi":"10.1371/journal.pone.0174161","title":"Classifying three imaginary states of the same upper extremity using time-domain features","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Brain–computer interface; Support vector machine; Computer science; Artificial intelligence; Exoskeleton; Radial basis function; Kernel (algebra); Electroencephalography; Pattern recognition (psychology); Task (project management); Radial basis function kernel; Artificial neural network; Simulation; Kernel method; Mathematics; Medicine","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":[0.0003314527,0.0005082255,0.0003500778,0.001080907,0.0001985644,0.0005246109,0.0002299413,0.0005385053,0.001089643],"category_scores_gemma":[0.001838294,0.00007271428,0.0003447449,0.0006123045,0.0002518691,0.0004622963,0.0003265958,0.0002568602,0.0003817078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157408,"about_ca_system_score_gemma":0.0001696291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008528495,"about_ca_topic_score_gemma":0.001397871,"domain_scores_codex":[0.9997326,0.00004217024,0.00002993085,0.000078705,0.00007818155,0.00003850814],"domain_scores_gemma":[0.9993724,0.0002496355,0.0001023523,0.00006521049,0.0001734044,0.0000369608],"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":[0.0008726877,0.0004237613,0.04564633,0.0003271742,0.0002090728,0.0005428564,0.0002892128,0.01019739,0.2030905,0.001093217,0.002321346,0.7349865],"study_design_scores_gemma":[0.0001186114,0.001120243,0.4623795,0.0001453508,0.0003630163,0.004430444,0.001042586,0.4002944,0.1174664,0.006175944,0.006325489,0.0001380551],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8335814,0.0005910263,0.1615318,0.0001817926,0.0001092754,0.00009679067,0.000475347,0.000388186,0.003044297],"genre_scores_gemma":[0.9778685,0.0001730215,0.0207626,0.00003840506,0.00002706956,0.00003291312,0.000369319,0.00001518649,0.0007131088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001089643,"threshold_uncertainty_score":0.003645182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08291294604852514,"score_gpt":0.2843433980196276,"score_spread":0.2014304519711025,"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."}}