{"id":"W2552191980","doi":"","title":"Simulation of a Kinematic Calibration Procedure that Employs the Relative Measurement Concept","year":2004,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Calibration; Robot calibration; Kinematics; Repeatability; Computer science; Approximation error; Singular value decomposition; Computer vision; Artificial intelligence; Simulation; Robot kinematics; Algorithm; Mathematics; Mobile robot; Statistics; Physics","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":[0.0006325407,0.0003623173,0.0003166427,0.0003749695,0.0004291156,0.0004013605,0.000713813,0.0006738311,0.004385238],"category_scores_gemma":[0.001485199,0.0002069331,0.0003562616,0.0003475273,0.0004445998,0.0004148135,0.0003519115,0.0005208664,0.0003600423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004184018,"about_ca_system_score_gemma":0.0007245843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005862022,"about_ca_topic_score_gemma":0.004178228,"domain_scores_codex":[0.9998211,0.00004121749,0.000008234595,0.00002424554,0.00007687454,0.00002833388],"domain_scores_gemma":[0.999353,0.0003110204,0.00007307768,0.0001126004,0.0001306119,0.00001974218],"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":[0.00008944232,0.00006962235,0.001324422,0.00006086043,0.00001324127,0.00006645788,0.00008696555,0.9737657,0.00429609,0.006300002,0.0003332389,0.01359402],"study_design_scores_gemma":[0.00001933345,0.000075216,0.0003034302,0.000005973224,0.000004670412,0.00002212684,0.00002298855,0.9945999,0.00346904,0.0005115839,0.0009585441,0.000007208265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4708983,0.0001049157,0.5089931,0.000207666,0.0001205079,0.0002899849,0.0005296722,0.002174748,0.01668115],"genre_scores_gemma":[0.9086676,0.00007498184,0.08832907,0.00002551459,0.00000558936,0.0001559555,0.0002985512,0.00008796043,0.002354617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005862022,"threshold_uncertainty_score":0.01467007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03023319420571442,"score_gpt":0.2250014550787012,"score_spread":0.1947682608729868,"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."}}