{"id":"W3165466478","doi":"10.1038/s41598-021-90688-4","title":"Intuitive real-time control strategy for high-density myoelectric hand prosthesis using deep and transfer learning","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Interdisciplinary Research in Rehabilitation; Université du Québec à Montréal; Université Laval","funders":"","keywords":"Transfer of learning; Computer science; Transfer (computing); Control (management); Artificial intelligence; Machine learning; Physical medicine and rehabilitation; Medicine; Operating system","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":[0.0003100661,0.0004420895,0.0002204173,0.0001403884,0.0001179937,0.0002567522,0.0004399075,0.0003352405,0.001479921],"category_scores_gemma":[0.0006605491,0.0001543746,0.0001746056,0.00009410291,0.0002083317,0.0003241706,0.0004846832,0.0003203218,0.000298643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001954489,"about_ca_system_score_gemma":0.0002497601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001417456,"about_ca_topic_score_gemma":0.002164289,"domain_scores_codex":[0.9998342,0.00002446911,0.00001180926,0.00004359777,0.00005959382,0.0000262884],"domain_scores_gemma":[0.9998323,0.00006142546,0.00002990915,0.00002717565,0.00003741105,0.00001178096],"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":[0.0003127775,0.0002964921,0.002111074,0.0001656295,0.00005077744,0.0003127065,0.0001730928,0.09207939,0.3312187,0.001062629,0.001490188,0.5707266],"study_design_scores_gemma":[0.00002405213,0.0004501558,0.004873534,0.00001690967,0.00002546469,0.0002425344,0.00002938238,0.9190613,0.07280401,0.0009506528,0.001499617,0.00002240253],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1573105,0.0002313473,0.8375025,0.0001131878,0.00005067969,0.0001051183,0.00003840257,0.002076637,0.002571624],"genre_scores_gemma":[0.9419352,0.0000531199,0.05590938,0.00007253832,0.00001093298,0.00005892422,0.000039566,0.00003084752,0.001889456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001479921,"threshold_uncertainty_score":0.004950821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056148785329492,"score_gpt":0.2124951723211388,"score_spread":0.2019336844678439,"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."}}