{"id":"W2012484016","doi":"10.1115/detc2005-85034","title":"On Performance Enhancement of Parallel Kinematic Machine","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Ontario Tech University","funders":"","keywords":"Kinematics; Computer science; Torque; Degrees of freedom (physics and chemistry); Kinematic chain; Mechanism (biology); Machining; Motion control; Machine tool; Kinematic diagram; Control engineering; Artificial intelligence; Engineering; Mechanical engineering; Robot","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":[0.0004445905,0.0003736221,0.0003178353,0.0002809091,0.0002023396,0.0003858588,0.0004764023,0.0002937496,0.002914827],"category_scores_gemma":[0.001142098,0.00009618419,0.0002077729,0.0002672379,0.0003287096,0.0007840934,0.0004731951,0.0003326128,0.0008218815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001844415,"about_ca_system_score_gemma":0.0001852339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002692947,"about_ca_topic_score_gemma":0.0001460973,"domain_scores_codex":[0.9995209,0.00009473095,0.00001571552,0.00006330116,0.0002580261,0.00004723599],"domain_scores_gemma":[0.9995846,0.000146034,0.00005189238,0.00007507862,0.0001272491,0.000015215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003218828,0.0001200627,0.001389362,0.0004492618,0.0000272721,0.0003591289,0.0001889996,0.20843,0.1278987,0.05521553,0.002251242,0.6033486],"study_design_scores_gemma":[0.00004239737,0.001048804,0.001580432,0.00004712394,0.0000373089,0.0007599154,0.00005072728,0.8710443,0.07510058,0.01500883,0.03524,0.00003954158],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05939872,0.001985677,0.9076352,0.0001856845,0.0001231017,0.00003208752,0.00001463784,0.001447586,0.02917737],"genre_scores_gemma":[0.9168027,0.0009293357,0.0770282,0.00004985472,0.0001214169,0.00003122427,0.00004009907,0.00008084075,0.004916226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002914827,"threshold_uncertainty_score":0.009751022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006144490241026593,"score_gpt":0.1913598750886589,"score_spread":0.1852153848476323,"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."}}