{"id":"W3214338023","doi":"10.1016/j.ifacol.2021.08.021","title":"Numerical Versus Analytical Direct Kinematics in a Novel 4-DOF Parallel Robot Designed for Digital Metrology","year":2021,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Inverse kinematics; Kinematics; Forward kinematics; Computer science; Robot kinematics; Nonlinear system; Robot; Parallel manipulator; Control theory (sociology); Numerical analysis; Artificial neural network; Artificial intelligence; Mathematics; Mobile robot; Mathematical analysis; Classical mechanics; 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":[0.0002365416,0.0002627747,0.000239593,0.0001985935,0.0002305786,0.000295375,0.0004263875,0.0004440382,0.001334619],"category_scores_gemma":[0.0004626867,0.0001708308,0.0002611201,0.0001993298,0.0004208495,0.0003476176,0.0003405511,0.0002900336,0.000188498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001908346,"about_ca_system_score_gemma":0.0005699549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007316929,"about_ca_topic_score_gemma":0.0008693765,"domain_scores_codex":[0.9998839,0.00001803977,0.000004870366,0.00001886475,0.00006482417,0.000009503565],"domain_scores_gemma":[0.9998772,0.0000311117,0.00003479901,0.0000239357,0.00002461842,0.000008192648],"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":[0.00021182,0.00008991735,0.002382538,0.000543003,0.00003554257,0.00053239,0.0002427314,0.7203199,0.1237471,0.03582618,0.0008602107,0.1152087],"study_design_scores_gemma":[0.00003341294,0.0002714186,0.0008448006,0.0000221112,0.00001291217,0.0003072013,0.00005227977,0.9794834,0.01200125,0.00249991,0.004455284,0.00001596156],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09784436,0.0004589988,0.891683,0.0001840846,0.00009203143,0.00007124604,0.0000375267,0.0003757288,0.009252959],"genre_scores_gemma":[0.6555259,0.0002654867,0.3403592,0.00002639116,0.00001268639,0.00009335719,0.00003558584,0.00001993491,0.003661374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001334619,"threshold_uncertainty_score":0.004464686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902605033064512,"score_gpt":0.2613935155387092,"score_spread":0.2323674652080641,"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."}}