{"id":"W2398336359","doi":"10.2316/journal.206.2015.5.206-4391","title":"OPTIMAL CALIBRATION AND IDENTIFICATION OF A 2-DOF PARALLEL MANIPULATOR WITH REDUNDANT ACTUATION","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Youth Innovation Promotion Association; State Key Laboratory of Mechanical System and Vibration; Youth Innovation Promotion Association of the Chinese Academy of Sciences; University of Science and Technology of China; National Natural Science Foundation of China","keywords":"Parallel manipulator; Identification (biology); Calibration; Computer science; Manipulator (device); Control theory (sociology); Artificial intelligence; Mathematics; Robot","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0001831306,0.00006714325,0.00009812055,0.0001384083,0.0000162087,0.00007990121,0.00005919622,0.00003639932,0.000002314833],"category_scores_gemma":[0.00003038114,0.000056534,0.00001376673,0.00004376286,0.00002060794,0.0004789626,0.0000100351,0.00005087144,1.960011e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003581749,"about_ca_system_score_gemma":0.00002635988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003326602,"about_ca_topic_score_gemma":0.000001468248,"domain_scores_codex":[0.9992666,0.00000930106,0.000351248,0.00005527256,0.0002724821,0.00004514775],"domain_scores_gemma":[0.999297,0.00001538906,0.0002720699,0.00003836923,0.0003316476,0.00004557347],"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":[0.00003581299,0.00001493271,0.0004375745,0.00002927095,0.00004472761,0.000001644658,0.0004739414,0.9941755,0.001067919,0.0007211393,0.00003222633,0.002965308],"study_design_scores_gemma":[0.0005890646,0.00008020869,0.007215838,0.00006822499,0.00002861326,0.00007023518,0.0001169617,0.9855658,0.005613079,0.0005481181,0.00003485567,0.00006899853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4284619,0.0001109233,0.5709544,0.0002010116,0.0001750097,0.00004789788,0.000002208159,0.00001612531,0.00003056462],"genre_scores_gemma":[0.9757825,0.0001367021,0.02397251,0.000006938831,0.00006307427,0.000001199779,0.00001583212,0.000008826124,0.00001241221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5473206,"threshold_uncertainty_score":0.230539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414268863909217,"score_gpt":0.2316730358939348,"score_spread":0.2175303472548426,"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."}}