{"id":"W3140801635","doi":"10.1016/j.rcim.2021.102158","title":"Kinematic calibration of a 3-PRRU parallel manipulator based on the complete, minimal and continuous error model","year":2021,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Science Foundation of Zhejiang Province","keywords":"Parallel manipulator; Kinematics; Manipulator (device); Calibration; Computer science; Control theory (sociology); Control engineering; Artificial intelligence; Mathematics; Robot; Engineering; Control (management); Physics; Statistics; Classical mechanics","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":[0.0005504435,0.000673702,0.0007906009,0.000466778,0.000566289,0.0006598661,0.001031191,0.001012104,0.002580685],"category_scores_gemma":[0.0008598874,0.0005542582,0.0005207183,0.0005023059,0.0005710182,0.0007524083,0.001068454,0.0007254684,0.0007929712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002906753,"about_ca_system_score_gemma":0.0009082789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002093648,"about_ca_topic_score_gemma":0.002165985,"domain_scores_codex":[0.9994624,0.00008051272,0.00002076448,0.0001692878,0.0002381615,0.00002892695],"domain_scores_gemma":[0.9997074,0.00003467221,0.0000736861,0.00008488241,0.00008524763,0.00001420463],"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":[0.0002650123,0.0000629104,0.001109813,0.0003020298,0.00009295187,0.0003949,0.0002705868,0.7278309,0.07958762,0.02208992,0.001357759,0.1666356],"study_design_scores_gemma":[0.00003723791,0.0002407127,0.001696593,0.00003829939,0.00003218216,0.0004204326,0.00004132563,0.9696927,0.0164657,0.004890471,0.006388318,0.00005598235],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02178206,0.0000873074,0.9732881,0.00006354431,0.00003051097,0.00003712224,0.0000414857,0.0007681655,0.003901626],"genre_scores_gemma":[0.7173647,0.0001656904,0.2780285,0.00004397306,0.00002194178,0.0001186213,0.0001671885,0.00009331051,0.003996008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002580685,"threshold_uncertainty_score":0.008633196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016053909008805,"score_gpt":0.1996569755892107,"score_spread":0.1794964364991227,"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."}}