{"id":"W2150474239","doi":"10.1109/robot.1987.1087926","title":"Computational scheme for simulating robot manipulators","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Jacobian matrix and determinant; Differential algebraic equation; Scheme (mathematics); Degrees of freedom (physics and chemistry); Topology (electrical circuits); Robot kinematics; Robot manipulator; Dimension (graph theory); Matrix (chemical analysis); Computer science; Algebraic number; Robot; Set (abstract data type); Differential (mechanical device); Control theory (sociology); Mathematics; Parallel manipulator; Applied mathematics; Differential equation; Mathematical analysis; Ordinary differential equation; Mobile robot; Artificial intelligence; Pure mathematics; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004143835,0.00006556447,0.00006777472,0.00002449032,0.0000354507,0.00001710777,0.00004097904,0.00003340395,0.00009662984],"category_scores_gemma":[0.000006888857,0.00006456634,0.00003326533,0.00003469421,0.000003070819,0.00006092116,0.000007833767,0.00003272556,0.00002822691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002673034,"about_ca_system_score_gemma":0.000003924871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.897329e-7,"about_ca_topic_score_gemma":0.000003334103,"domain_scores_codex":[0.9996199,0.00000127278,0.0001217806,0.00007022745,0.0000627551,0.000124062],"domain_scores_gemma":[0.9998347,0.00004539052,0.000008543987,0.00005597527,0.00001857217,0.00003685453],"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":[5.58148e-7,0.000003722767,0.00003214757,0.00001039804,0.000007231501,1.022727e-7,0.00001262615,0.9156958,0.0001187386,0.08067312,0.0001565073,0.003289078],"study_design_scores_gemma":[0.0001804179,0.000006908247,0.00007472489,0.000003516622,0.00000258014,0.000001123609,0.00001010675,0.995386,0.00006749055,0.003752977,0.0004266445,0.00008752442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007190754,0.00001328832,0.9893551,0.0000550823,0.00009973743,0.00009515861,0.00000151084,0.0002290446,0.002960268],"genre_scores_gemma":[0.3549892,3.424431e-7,0.6446409,0.0000566283,0.00007600689,0.000003881233,0.000009986717,0.00001365368,0.0002094728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3477984,"threshold_uncertainty_score":0.2632939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609100472263112,"score_gpt":0.2364960398333462,"score_spread":0.2204050351107151,"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."}}