{"id":"W2056240245","doi":"10.1016/s0021-9290(00)00142-1","title":"A method for measuring endpoint stiffness during multi-joint arm movements","year":2000,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":176,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Exploratory Research for Advanced Technology; Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Stiffness; Joint stiffness; Joint (building); Computer science; Displacement (psychology); Control theory (sociology); Trajectory; Amplitude; Simulation; Structural engineering; Engineering; Physics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001257334,0.0009286971,0.0007199398,0.001896502,0.0006769313,0.0007222232,0.0009059907,0.001436522,0.002863923],"category_scores_gemma":[0.002772899,0.0008134507,0.0004055964,0.001306205,0.0005280577,0.0009174293,0.000757538,0.0009927565,0.0009873554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000287775,"about_ca_system_score_gemma":0.0007569946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001574923,"about_ca_topic_score_gemma":0.004805238,"domain_scores_codex":[0.998793,0.0001873083,0.00006763096,0.0002707202,0.0006190701,0.00006226654],"domain_scores_gemma":[0.9969476,0.001472816,0.0002824944,0.000313575,0.0007933083,0.0001902336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008197578,0.0001154849,0.003747828,0.0004244047,0.00006501032,0.000101795,0.0001826678,0.0004287363,0.8346353,0.0003563938,0.0007353302,0.1583874],"study_design_scores_gemma":[0.0005796138,0.003409767,0.1534909,0.0003187671,0.0006536882,0.007786558,0.0004083969,0.05292939,0.7620113,0.002042181,0.01573202,0.0006374396],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09503844,0.001762062,0.8971493,0.0001298672,0.0003107455,0.0004810326,0.0008104928,0.001275938,0.003042126],"genre_scores_gemma":[0.3792165,0.001401232,0.6109409,0.0001807299,0.0001296931,0.00110372,0.0004401719,0.0002971076,0.006289872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002863923,"threshold_uncertainty_score":0.009580731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0810095317036898,"score_gpt":0.2983802537654569,"score_spread":0.2173707220617671,"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."}}