{"id":"W4311164922","doi":"10.18280/ts.390518","title":"A New Feature Extraction Method for EMG Signals","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Classifier (UML); Pattern recognition (psychology); Artificial intelligence; Feature extraction; Computer science; Support vector machine; Feature (linguistics); Quadratic classifier; Speech recognition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005511679,0.0009131634,0.001068741,0.00209111,0.0003598668,0.000772257,0.0007261345,0.0007442889,0.003407609],"category_scores_gemma":[0.001576986,0.0002972168,0.001104096,0.002245914,0.0002610907,0.001246554,0.0005681268,0.0007310449,0.001995985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002461094,"about_ca_system_score_gemma":0.0003774035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001063043,"about_ca_topic_score_gemma":0.001007095,"domain_scores_codex":[0.9989813,0.00007172166,0.0001112163,0.0002744471,0.0005014398,0.00005985338],"domain_scores_gemma":[0.9994131,0.0001385493,0.00005676341,0.00006385479,0.0003071983,0.00002067377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001273197,0.00004862107,0.0007362165,0.0003327749,0.00006302905,0.0001678564,0.00006559486,0.001615326,0.1260245,0.001373203,0.004418483,0.865027],"study_design_scores_gemma":[0.0001827512,0.001231035,0.0408828,0.0003033497,0.0004876192,0.006333319,0.0002319464,0.4579848,0.2870156,0.00690187,0.1980334,0.0004112957],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007019723,0.0009498857,0.9886132,0.0001029612,0.0003046851,0.0001424703,0.0004072219,0.001534837,0.0009250283],"genre_scores_gemma":[0.08994962,0.001128033,0.9003965,0.0001436246,0.0002435293,0.0004595929,0.001491659,0.000232119,0.005955288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003407609,"threshold_uncertainty_score":0.01139957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0171963122190666,"score_gpt":0.2673135964331301,"score_spread":0.2501172842140635,"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."}}