{"id":"W2781720005","doi":"","title":"Investigation of Optimum Pattern Recognition Methods for Robust Myoelectric Control During Dynamic Limb Movement","year":2017,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Linear discriminant analysis; Pattern recognition (psychology); Artificial intelligence; Classifier (UML); Robustness (evolution); Computer science; Quadratic classifier; Speech recognition; Dynamic time warping","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":[0.001359619,0.0004633923,0.0006590604,0.0005558928,0.0001312986,0.0005730215,0.0003962542,0.0004525828,0.001133119],"category_scores_gemma":[0.003874546,0.0002007789,0.0003939793,0.0004759777,0.0002029256,0.0007854118,0.0002070377,0.0004019825,0.0004179825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283435,"about_ca_system_score_gemma":0.000351859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008778839,"about_ca_topic_score_gemma":0.0009482178,"domain_scores_codex":[0.9994272,0.0001198332,0.00006566815,0.0001653492,0.0001842687,0.00003774574],"domain_scores_gemma":[0.9985766,0.0007530634,0.0001670348,0.0000766541,0.0004023338,0.00002430918],"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":[0.0003575914,0.0001428556,0.001572136,0.0003001087,0.00007370186,0.0000577632,0.00007240114,0.0515232,0.08015064,0.00136945,0.0005219647,0.8638583],"study_design_scores_gemma":[0.00002983564,0.0004577933,0.004866824,0.00003062277,0.00005164098,0.0001880015,0.00004852035,0.9641331,0.02831823,0.0006575088,0.001198532,0.00001940983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08455401,0.001564072,0.9121716,0.0001194058,0.00004734274,0.00008830914,0.00005820208,0.0004778274,0.0009192924],"genre_scores_gemma":[0.5672808,0.0009427794,0.4299851,0.00004538267,0.00004880053,0.0001583503,0.0001342047,0.00006406211,0.001340536],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001359619,"threshold_uncertainty_score":0.007190406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02602418083930397,"score_gpt":0.265826342729945,"score_spread":0.2398021618906411,"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."}}