{"id":"W2905689099","doi":"10.1109/jtehm.2018.2883943","title":"EMG Pattern Recognition Control of the DEKA Arm: Impact on User Ratings of Satisfaction and Usability","year":2018,"lang":"en","type":"article","venue":"IEEE Journal of Translational Engineering in Health and Medicine","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research","funders":"U.S. Department of Veterans Affairs","keywords":"Usability; Physical medicine and rehabilitation; Inertial measurement unit; Patient satisfaction; Physical therapy; Amputation; Computer science; Medicine; Psychology; Human–computer interaction; Artificial intelligence; 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":[0.001384544,0.0003044919,0.0003734989,0.0003113719,0.0001381516,0.0004467034,0.0001642877,0.0002264283,0.002663005],"category_scores_gemma":[0.006402119,0.0001010727,0.0003846085,0.0002334239,0.0002184523,0.0002682344,0.0003547277,0.00022489,0.000308341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001135432,"about_ca_system_score_gemma":0.00008375329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006952321,"about_ca_topic_score_gemma":0.000721272,"domain_scores_codex":[0.9986398,0.0006741547,0.0001229527,0.0001121469,0.0003386531,0.0001122529],"domain_scores_gemma":[0.9954773,0.002354011,0.0007104896,0.0002827597,0.0007132625,0.0004623301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0121132,0.003467434,0.7571926,0.0004340459,0.000358538,0.0005580155,0.002674563,0.0009388523,0.0366143,0.0000844453,0.0008838183,0.1846802],"study_design_scores_gemma":[0.0001194112,0.01151369,0.9796832,0.00001806723,0.0000962506,0.0007565789,0.001267282,0.002114849,0.003756005,0.000024328,0.0006208628,0.00002943916],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990512,0.0000603869,0.0003245695,0.00001134608,0.000003466139,0.00001214973,0.00002590702,0.000009677793,0.0005013333],"genre_scores_gemma":[0.9992506,0.00003519208,0.0002567133,0.00001457247,0.000004366132,0.00001192911,0.0000444599,0.000003732646,0.0003784297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002663005,"threshold_uncertainty_score":0.008908689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603874594654066,"score_gpt":0.2677168527312792,"score_spread":0.2516781067847386,"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."}}