{"id":"W1987433044","doi":"10.3389/fncom.2013.00120","title":"Robustness of muscle synergies during visuomotor adaptation","year":2013,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Isometric exercise; Electromyography; Robustness (evolution); Computer science; Physical medicine and rehabilitation; Motor control; Elbow; Artificial intelligence; Mathematics; Psychology; Anatomy; Neuroscience; Medicine; Physical therapy; Biology","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":[0.0003882805,0.0002604309,0.0003053737,0.000269481,0.0001013521,0.0001953382,0.0001110151,0.0002288276,0.0008442014],"category_scores_gemma":[0.003057799,0.0002329541,0.0001728016,0.0001166876,0.0002408095,0.0001842033,0.0003256304,0.0002124688,0.0001648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009655343,"about_ca_system_score_gemma":0.00008600188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008257295,"about_ca_topic_score_gemma":0.0007072328,"domain_scores_codex":[0.9998114,0.00003674664,0.00001452163,0.00006467751,0.00003941158,0.00003325352],"domain_scores_gemma":[0.9993396,0.000311767,0.0001068765,0.000116346,0.00006298585,0.00006232469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009653305,0.00006018056,0.007899112,0.00005190234,0.00006533903,0.00009977959,0.0001719228,0.003239048,0.961925,0.00003044031,0.0000447906,0.02544728],"study_design_scores_gemma":[0.00005667356,0.001387525,0.9176335,0.00001215956,0.00006215783,0.0004668801,0.0001148551,0.020927,0.05868272,0.0002888336,0.0003352817,0.00003250642],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965041,0.00007357955,0.003019779,0.00001121028,0.000003386205,0.00001360712,0.00004784836,0.0000570927,0.0002694232],"genre_scores_gemma":[0.9988573,0.00003030463,0.000812655,0.000005615188,0.000002412171,0.00001090558,0.00008947935,0.00001207165,0.000179342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008442014,"threshold_uncertainty_score":0.002824187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191125421640812,"score_gpt":0.2299287101392388,"score_spread":0.2080174559228307,"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."}}