{"id":"W1528586140","doi":"10.1007/978-3-540-39676-5_9","title":"Guiding Movements without Redundancy Problems","year":2004,"lang":"en","type":"book-chapter","venue":"Understanding complex systems","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Montreal Neurological Institute and Hospital","funders":"","keywords":"Kinematics; Redundancy (engineering); Control theory (sociology); Motor control; Computer science; Parametric statistics; Neurophysiology; Control engineering; Engineering; Control (management); Mathematics; Artificial intelligence; Neuroscience; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001998013,0.0008002255,0.0004378535,0.0002652882,0.000321148,0.0007376742,0.0007168477,0.0007911887,0.007716562],"category_scores_gemma":[0.0005251815,0.0003641769,0.0002429749,0.000312151,0.0008278713,0.001698236,0.0006439749,0.001092576,0.00268578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003427833,"about_ca_system_score_gemma":0.0003684158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007635818,"about_ca_topic_score_gemma":0.001200834,"domain_scores_codex":[0.999895,0.00001480189,0.000005082642,0.00002992327,0.0000449721,0.00001023907],"domain_scores_gemma":[0.9999073,0.00003408914,0.000006728232,0.0000248963,0.00001926058,0.000007771328],"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":[0.00006102124,0.00002633908,0.0001049783,0.0002081183,0.00002366099,0.00009075055,0.0002260778,0.03377141,0.02277447,0.5511223,0.02291353,0.3686773],"study_design_scores_gemma":[0.00002017004,0.00006282527,0.000351451,0.0001211456,0.00002148286,0.0002405411,0.00006540462,0.1022902,0.01471328,0.6594452,0.2226349,0.00003342221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00866812,0.002985927,0.8006608,0.0008467399,0.0004333497,0.00002941699,0.0001010029,0.001082543,0.1851921],"genre_scores_gemma":[0.2210873,0.005522019,0.4654182,0.0006176556,0.0003342766,0.0001961486,0.0004128647,0.0008313263,0.3055802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007716562,"threshold_uncertainty_score":0.02581447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2753852543239365,"score_gpt":0.2852681278312297,"score_spread":0.009882873507293166,"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."}}