{"id":"W2614985414","doi":"10.3389/fncom.2017.00035","title":"Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions","year":2017,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Qatar National Research Fund; Fonds Québécois de la Recherche sur la Nature et les Technologies; McGill University; Fonds National de la Recherche Luxembourg; Qatar Foundation","keywords":"Control theory (sociology); Joint stiffness; Stretch reflex; Torque; Ankle; Isometric exercise; Stiffness; Reflex; Nonlinear system; Mathematics; Computer science; Physics; Engineering; Structural engineering; Medicine; Anatomy; Physical therapy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000118123,0.0001111587,0.0001684631,0.000277527,0.0004088741,0.00007382475,0.0002435855,0.00003040925,0.000002928934],"category_scores_gemma":[0.0001765674,0.0001279074,0.00005270677,0.0002192256,0.000166792,0.0005566549,0.00003318877,0.0001488325,9.038806e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006216284,"about_ca_system_score_gemma":0.00001919199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008938853,"about_ca_topic_score_gemma":0.000001011016,"domain_scores_codex":[0.998982,0.00002080405,0.000335569,0.0002340043,0.0002338371,0.0001937659],"domain_scores_gemma":[0.9994745,0.00005933707,0.0001558469,0.0002096166,0.00006395663,0.00003670845],"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":[0.00001839846,0.00005849149,0.009812258,0.00007512438,0.00001943113,0.000005754239,0.0001819635,0.8284848,0.1522931,0.0000324282,0.0001528097,0.008865419],"study_design_scores_gemma":[0.0001602567,0.000004008027,0.4599829,0.00001786443,0.000003492619,0.00000282067,0.000008167759,0.5381117,0.00118415,0.000442107,0.000009320178,0.00007315398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8015386,0.00005328092,0.1967225,0.0001609165,0.001156078,0.0001520922,0.00001598564,0.00007713405,0.0001233888],"genre_scores_gemma":[0.9951138,0.00002679183,0.004746619,0.00002755997,0.00001918838,0.00001623706,0.000007404773,0.00001271436,0.00002968596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4501706,"threshold_uncertainty_score":0.5215914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462791907824891,"score_gpt":0.2464216964685364,"score_spread":0.2317937773902875,"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."}}