{"id":"W1594419525","doi":"10.1109/aim.2015.7222553","title":"Kinematic analysis and optimization for 4PUS-RPU mechanism","year":2015,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Workspace; Particle swarm optimization; Mechanism (biology); Kinematics; Computer science; Global optimization; Mathematical optimization; Compliant mechanism; Rigidity (electromagnetism); Control theory (sociology); Engineering; Mathematics; Finite element method; Artificial intelligence; Robot; Physics; Structural engineering","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":[0.0006421256,0.0005760753,0.0008501869,0.0007223777,0.000438632,0.0006575969,0.0005979235,0.000738672,0.002259761],"category_scores_gemma":[0.000599914,0.0004706591,0.00106709,0.0004603417,0.0004630388,0.0004876525,0.0005339032,0.0003236579,0.0002846696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003443778,"about_ca_system_score_gemma":0.0008069886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001998002,"about_ca_topic_score_gemma":0.001253906,"domain_scores_codex":[0.9997438,0.00006149856,0.0000154069,0.00004219493,0.0001094121,0.00002781504],"domain_scores_gemma":[0.9998318,0.00004671249,0.00004642382,0.00002321914,0.00004375846,0.000008169198],"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":[0.00002294936,0.00001176796,0.000404372,0.00006186969,0.00001636567,0.00008551503,0.00001975041,0.9776701,0.004842202,0.004161668,0.0001061697,0.01259731],"study_design_scores_gemma":[0.000005588994,0.00003799559,0.0003580492,0.000006580516,0.000008050354,0.00003055644,0.00001215648,0.9973847,0.0008320373,0.0009382151,0.0003798449,0.000006134774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0563036,0.0003681146,0.936079,0.0001100494,0.00003671461,0.00006225285,0.00004716048,0.0001661523,0.00682697],"genre_scores_gemma":[0.8716919,0.0004362268,0.1226249,0.00003704954,0.00001789449,0.0002482906,0.00009506888,0.00006377919,0.004784811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002259761,"threshold_uncertainty_score":0.007559657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461762364769843,"score_gpt":0.2109218676578941,"score_spread":0.1963042440101957,"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."}}