{"id":"W2093266077","doi":"10.1109/ccece.2008.4564841","title":"An EMG-based force control system for prosthtic arms","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kinematics; Robotic arm; Controller (irrigation); Robot; Computer science; Simulation; Control theory (sociology); Control system; Engineering; Control (management); Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008685629,0.0003745732,0.0003977473,0.0004516993,0.0002413132,0.0001761016,0.0002436743,0.0001453545,0.000006516072],"category_scores_gemma":[0.00001784303,0.00037709,0.00007297247,0.0003759429,0.00004707999,0.0002152361,0.000006324318,0.0002916249,0.000001843246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001823789,"about_ca_system_score_gemma":0.0001849723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002078447,"about_ca_topic_score_gemma":0.000147838,"domain_scores_codex":[0.9983346,0.000005388726,0.0002738586,0.0004220256,0.0001717134,0.000792408],"domain_scores_gemma":[0.9989124,0.00005780564,0.00003932697,0.0001193314,0.0002825803,0.0005885442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005848709,0.0004560362,0.02375928,0.004933876,0.001462267,0.0001560132,0.006494386,0.07209529,0.06635834,0.4976197,0.007134432,0.3189455],"study_design_scores_gemma":[0.0007672442,0.0005098186,0.008014426,0.0001079785,0.00001996724,0.00002854472,0.0000331667,0.9882234,0.001175539,0.00007594666,0.0005602275,0.0004837264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3415028,0.0002130247,0.6530179,0.0006199016,0.0003942995,0.001437977,0.0000457212,0.00149957,0.001268712],"genre_scores_gemma":[0.9977309,0.00003091644,0.001515325,0.0002096804,0.0001731437,0.000269183,0.00001160914,0.00004621374,0.00001305241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9161281,"threshold_uncertainty_score":0.9998681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242670059782099,"score_gpt":0.1822784968725729,"score_spread":0.1698517962747519,"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."}}