{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003688424,0.00007464212,0.0002215774,0.0001454748,0.00002250733,0.000001458269,0.00002035393,0.00002822885,0.000008624642],"category_scores_gemma":[0.00006905722,0.00004902625,0.00003373584,0.0001298867,0.00005285766,0.00006560643,7.887784e-7,0.0001441744,1.558488e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002292334,"about_ca_system_score_gemma":0.00002674942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007235848,"about_ca_topic_score_gemma":0.00002170803,"domain_scores_codex":[0.9992462,0.00002369069,0.0004406975,0.00004496868,0.0001553613,0.00008907844],"domain_scores_gemma":[0.9994871,0.0002017182,0.0001264928,0.0000369142,0.00008626706,0.00006149298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005816699,0.00008964263,0.5244754,0.001986047,0.0002971991,8.146026e-7,0.005601812,0.06814285,0.02226148,0.00007606656,0.0003056816,0.3761813],"study_design_scores_gemma":[0.001594013,0.0007755859,0.9821635,0.0006148624,0.00001257156,0.00001405982,0.0000366499,0.01383898,0.0007571888,0.00009601846,0.0000509119,0.00004561179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838621,0.0005574989,0.01440439,0.0008615519,0.0001894794,0.0001043677,0.000005226446,0.000005080874,0.00001030578],"genre_scores_gemma":[0.9992651,0.0003509395,0.0001717916,0.00007019402,0.0001343367,0.000001356899,6.099883e-7,0.000005457804,2.454749e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4576881,"threshold_uncertainty_score":0.1999232,"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."}}