{"id":"W2066519883","doi":"10.1016/j.bspc.2007.11.005","title":"A training strategy to reduce classification degradation due to electrode displacements in pattern recognition based myoelectric control","year":2008,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":275,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Classifier (UML); Pattern recognition (psychology); Artificial intelligence; Autoregressive model; Training set; Electrode; Electrode array; Speech recognition; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002199416,0.0001767386,0.0002496882,0.0003895126,0.0001626104,0.00004632453,0.0000704871,0.00008754658,0.00001665408],"category_scores_gemma":[0.00004790935,0.0001694051,0.00003134551,0.0007859115,0.00003522311,0.0001274313,0.00000325587,0.0001734287,0.000003267514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008563962,"about_ca_system_score_gemma":0.00007366177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002536945,"about_ca_topic_score_gemma":0.00001574707,"domain_scores_codex":[0.998677,0.00005903155,0.0003205058,0.0002782055,0.0002690339,0.0003962766],"domain_scores_gemma":[0.9995481,0.00008094517,0.00004673587,0.00005783374,0.00006510997,0.0002013238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001353202,0.00006113628,0.0004409051,0.00003858304,0.00002418275,0.000005597331,0.0002254149,0.0001846602,0.08385542,0.00000135075,0.0001634142,0.914864],"study_design_scores_gemma":[0.009180231,0.001615488,0.2014884,0.0003875647,0.00008591001,0.00003756996,0.0003669646,0.7794636,0.005062473,0.0001642821,0.00121974,0.0009277376],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4221355,0.0002050975,0.5761558,0.0008505616,0.0000273306,0.000375485,0.00001036923,0.0001267741,0.000113056],"genre_scores_gemma":[0.9985772,0.00001474766,0.0001896546,0.0007941015,0.0001008297,0.0002585546,0.00003887152,0.00001944165,0.000006562368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9139363,"threshold_uncertainty_score":0.6908139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402303329662841,"score_gpt":0.2494141799716853,"score_spread":0.2153911466750569,"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."}}