{"id":"W1978961505","doi":"10.1002/rob.8112","title":"A dexterous humanoid shoulder mechanism","year":2001,"lang":"en","type":"article","venue":"Journal of Robotic Systems","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dalhousie University","keywords":"Mechanism (biology); Kinematics; Ball (mathematics); Joint (building); Universal joint; Computer science; Motion (physics); Shoulder joint; Humanoid robot; Simulation; Engineering; Artificial intelligence; Mathematics; Mechanical engineering; Physics; Structural engineering; Classical mechanics; Geometry; Anatomy; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003693048,0.0001794836,0.000432049,0.0001787587,0.00005019265,0.00009130254,0.0002441231,0.0001203069,0.00004486667],"category_scores_gemma":[0.00002213829,0.0001488647,0.0001397084,0.000149718,0.00001065726,0.0001669985,0.00001802037,0.0002330164,0.00003064861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001173829,"about_ca_system_score_gemma":0.00002964433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009281395,"about_ca_topic_score_gemma":0.000002881059,"domain_scores_codex":[0.9985584,0.00003719496,0.0006632943,0.00009292474,0.0003604826,0.0002876834],"domain_scores_gemma":[0.9992768,0.00004398608,0.0001801164,0.0002122753,0.0001197678,0.000167018],"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":[0.000005770492,0.00002286803,0.00008478572,0.00006381828,0.00008442411,0.0002528313,0.0001143292,0.9847087,0.001871148,0.01152432,0.0008373213,0.0004296597],"study_design_scores_gemma":[0.0008487821,0.0002709367,0.0001620771,0.0003572149,0.000121741,0.007240758,0.0004558305,0.9851791,0.0001034087,0.003881352,0.001014942,0.0003638763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01453137,0.001055151,0.9776701,0.00004181243,0.004761503,0.0001274341,5.269129e-7,0.00007876781,0.001733375],"genre_scores_gemma":[0.9741612,0.0002687421,0.02362994,0.00004351009,0.0007854329,0.000004137204,7.73971e-7,0.0000678603,0.00103837],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9596298,"threshold_uncertainty_score":0.6070524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499134678851407,"score_gpt":0.2174076252370441,"score_spread":0.20241627844853,"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."}}