{"id":"W3135491679","doi":"10.1016/j.bspc.2021.102523","title":"Higher order tensor decomposition for proportional myoelectric control based on muscle synergies","year":2021,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Matrix decomposition; Tensor (intrinsic definition); Computer science; Curse of dimensionality; Kinematics; Factorization; Matrix (chemical analysis); Tucker decomposition; Control theory (sociology); Pattern recognition (psychology); Artificial intelligence; Mathematics; Control (management); Algorithm; Tensor decomposition","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":[0.0002110494,0.0001696356,0.0002780937,0.00008588975,0.0003495624,0.0001069885,0.00007627301,0.0001294279,0.0002519653],"category_scores_gemma":[0.0001103608,0.0001360391,0.0000885239,0.0002745575,0.0001293737,0.00006065693,0.000006598462,0.0001341008,0.000006509902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000355646,"about_ca_system_score_gemma":0.0001916126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001430956,"about_ca_topic_score_gemma":5.484717e-7,"domain_scores_codex":[0.9986225,0.00006680135,0.0003443927,0.0003481772,0.0003479318,0.0002701376],"domain_scores_gemma":[0.9986234,0.0005834681,0.000138231,0.0001112849,0.0003732664,0.0001703041],"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":[0.002234682,0.007788631,0.0004869748,0.001550617,0.0004236626,0.00009783604,0.0001454669,0.0003075107,0.2753135,0.08512461,0.02652784,0.5999987],"study_design_scores_gemma":[0.02840715,0.001327493,0.00792073,0.0005868984,0.0008198985,0.00007540412,0.0001088096,0.763492,0.004183146,0.1243937,0.06744488,0.00123985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01453604,0.0003515319,0.9656917,0.01799596,0.00006795856,0.0006053384,0.0001275928,0.0002247425,0.0003991549],"genre_scores_gemma":[0.9884672,0.000002231766,0.00760356,0.002887771,0.0002773312,0.0003488765,0.00008329422,0.00002367088,0.0003060481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9739312,"threshold_uncertainty_score":0.5547512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831940918657405,"score_gpt":0.2994295976742046,"score_spread":0.2811101884876305,"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."}}