{"id":"W2093311953","doi":"10.1115/1.1828461","title":"Optimal Calibration of Parallel Kinematic Machines","year":2005,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Jacobian matrix and determinant; Workspace; Calibration; Machine tool; Kinematics; Computer science; Spurious relationship; Inverse; Inverse kinematics; Software; Stewart platform; Algorithm; Machining; Tripod (photography); Control theory (sociology); Mathematics; Artificial intelligence; Engineering; Applied mathematics; Geometry; Mechanical engineering; Robot","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001576825,0.001114446,0.001469946,0.001382055,0.0006843347,0.001046008,0.001187966,0.001038033,0.00193968],"category_scores_gemma":[0.006272125,0.0009428225,0.0007811476,0.000998528,0.001320658,0.00178656,0.002150626,0.001406669,0.0006390894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007211885,"about_ca_system_score_gemma":0.001292369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009332377,"about_ca_topic_score_gemma":0.0008163973,"domain_scores_codex":[0.997223,0.0005518089,0.000121246,0.0006899039,0.001276666,0.0001374359],"domain_scores_gemma":[0.9984725,0.0004386572,0.0003197364,0.0003406388,0.0003896652,0.00003882958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002222815,0.00005073646,0.001003942,0.0003134027,0.00007323455,0.0001677192,0.000269345,0.52359,0.02900315,0.04132973,0.001702219,0.4022742],"study_design_scores_gemma":[0.00003684055,0.0001572386,0.0006891722,0.00006420114,0.00003106377,0.0004262646,0.00006526068,0.9195689,0.02758547,0.03857608,0.01272235,0.0000770543],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002775047,0.000107881,0.996039,0.00002152136,0.00002144341,0.00001337913,0.000006273332,0.0001885177,0.0008269423],"genre_scores_gemma":[0.267617,0.0003303056,0.7297322,0.00006123876,0.00004809707,0.0001174421,0.00007131406,0.0001914355,0.001830934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00193968,"threshold_uncertainty_score":0.008339167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01916857105150857,"score_gpt":0.2302840644255831,"score_spread":0.2111154933740745,"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."}}