{"id":"W1841943710","doi":"10.1007/s12555-014-0038-z","title":"“Load balance” control for a humanoid musculoskeletal arm in table tennis movement","year":2015,"lang":"en","type":"article","venue":"International Journal of Control Automation and Systems","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Control theory (sociology); Actuator; Computer science; Redundancy (engineering); Balance (ability); Acceleration; Simulation; Human muscle; Control (management); Physical medicine and rehabilitation; Artificial intelligence; Physics; Anatomy; Skeletal muscle; Medicine","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":[0.00119616,0.000127286,0.0003234375,0.0002225442,0.00004263331,0.0001997108,0.0002239169,0.00005423481,0.00001144694],"category_scores_gemma":[0.0009444496,0.0001031093,0.00009750536,0.00007241542,0.00003006327,0.0005107265,0.00001033677,0.00009869292,0.000004888475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002266323,"about_ca_system_score_gemma":0.0002052445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000703838,"about_ca_topic_score_gemma":0.00001448961,"domain_scores_codex":[0.9979181,0.0001708372,0.0007840567,0.0001639487,0.0007932251,0.0001698519],"domain_scores_gemma":[0.9980838,0.0002843647,0.0006619734,0.00007141476,0.0007781012,0.0001204031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007790524,0.002031184,0.01843393,0.0003050681,0.0007304067,0.0003443571,0.005078517,0.1024113,0.6735593,0.1384798,0.004157321,0.04667827],"study_design_scores_gemma":[0.03481023,0.0007822004,0.009415735,0.000198903,0.00004781997,0.0001435386,0.0004922725,0.9315967,0.0003817917,0.002643545,0.01923251,0.0002547477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7367815,0.001332198,0.2455698,0.005000504,0.006425489,0.002078152,0.0001735714,0.000079969,0.002558753],"genre_scores_gemma":[0.998318,0.00001570165,0.00007335746,0.0007447107,0.0004903465,0.00006627835,0.000002364745,0.000009910336,0.0002793943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8291854,"threshold_uncertainty_score":0.4204673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02604490069086277,"score_gpt":0.288348413328277,"score_spread":0.2623035126374142,"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."}}