{"id":"W2097092203","doi":"10.1109/tbme.2010.2068298","title":"Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":254,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Isometric exercise; Forearm; Wrist; Electromyography; Artificial limbs; Computer science; Physical medicine and rehabilitation; Prosthetic hand; Upper limb; Lower limb; Artificial neural network; Artificial intelligence; Simulation; Biomedical engineering; Prosthesis; Medicine; Anatomy; Physical therapy; Surgery","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":[0.0004905463,0.0004862334,0.0003464645,0.0002356754,0.0001324701,0.0002469546,0.0004123664,0.0004152158,0.000835702],"category_scores_gemma":[0.001387885,0.0002369147,0.0001923261,0.0001686888,0.0001535224,0.0004032522,0.0003457484,0.0002509103,0.0001829427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001372062,"about_ca_system_score_gemma":0.0001837003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009405558,"about_ca_topic_score_gemma":0.001808123,"domain_scores_codex":[0.9996855,0.00005937961,0.00002098802,0.00008739032,0.0001269216,0.00001987087],"domain_scores_gemma":[0.9997122,0.0001274862,0.00005143559,0.00003983138,0.00005743152,0.00001161722],"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":[0.0004818934,0.0001094448,0.003652645,0.0001571063,0.00005773003,0.0001077708,0.0001406323,0.01814003,0.2443826,0.0004617416,0.0003116692,0.7319968],"study_design_scores_gemma":[0.00007182304,0.0007149655,0.0324934,0.0000403511,0.00007857023,0.001149357,0.0000587245,0.8305306,0.1311527,0.001181047,0.002467026,0.00006140497],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2101472,0.0003609216,0.7876239,0.00006737719,0.00003968641,0.00007728672,0.00004566536,0.0004333887,0.001204505],"genre_scores_gemma":[0.834968,0.0001224822,0.1634008,0.00002995351,0.00002286202,0.0000518644,0.00003873216,0.000025132,0.001340159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009405558,"threshold_uncertainty_score":0.002795756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01394320813292428,"score_gpt":0.2296522574382927,"score_spread":0.2157090493053685,"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."}}