{"id":"W2057637063","doi":"10.1109/tnsre.2011.2166405","title":"Predictor-Based Compensation for Electromechanical Delay During Neuromuscular Electrical Stimulation","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of General Medical Sciences","keywords":"Control theory (sociology); Functional electrical stimulation; Robustness (evolution); Nonlinear system; Computer science; Controller (irrigation); Instability; Lyapunov stability; Mathematics; Stimulation; Control (management); Physics; Neuroscience; Psychology; Artificial intelligence; Mechanics","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":[0.0001086886,0.0002085601,0.0002121434,0.0003268218,0.0001601744,0.00002990563,0.00005104368,0.00009945832,0.000005218812],"category_scores_gemma":[0.00001800759,0.0002102298,0.0001237777,0.0003085721,0.00002062734,0.0001822264,4.493466e-7,0.0001820234,5.205718e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008249997,"about_ca_system_score_gemma":0.000006520718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001101213,"about_ca_topic_score_gemma":0.000002386045,"domain_scores_codex":[0.9989582,0.00003278318,0.0003361669,0.0002423811,0.0001598899,0.0002706335],"domain_scores_gemma":[0.9993834,0.0002863269,0.00003497244,0.0001331296,0.00007450545,0.00008769507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000867221,0.00006859851,0.00009186508,0.0003593999,0.000082148,8.007217e-7,0.0002755142,0.9499451,0.04618821,0.000365676,0.00001578923,0.002520181],"study_design_scores_gemma":[0.0007861395,0.0005213263,0.02385908,0.00004508822,0.0000385834,0.000007181919,0.00002520034,0.9692489,0.005152325,0.00001907121,0.00006341915,0.0002337015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.510726,0.0000586903,0.4879878,0.00001644202,0.0003538651,0.000481851,0.000006625911,0.0003591772,0.000009580416],"genre_scores_gemma":[0.9978895,0.00001414186,0.001645547,0.000008319174,0.00004521042,0.0003408552,0.000004629454,0.00004529939,0.000006463916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4871635,"threshold_uncertainty_score":0.8572922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179837922548766,"score_gpt":0.1983383553823568,"score_spread":0.1865399761568691,"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."}}