{"id":"W2124536805","doi":"10.1109/tro.2015.2489502","title":"Spline Path Following for Redundant Mechanical Systems","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spline (mechanical); Mechanical system; Computer science; Path (computing); Algorithm; Mathematics; Control engineering; Mathematical optimization; Engineering; Artificial intelligence; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009677799,0.0001244827,0.0001530424,0.00005230404,0.00008012504,0.00003328217,0.00007108736,0.00007827878,0.000001370887],"category_scores_gemma":[0.000008194485,0.0001244022,0.00007522489,0.0001202177,0.000006443273,0.0001052289,3.802276e-7,0.000127931,0.000007984964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007789195,"about_ca_system_score_gemma":0.00002263938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002274365,"about_ca_topic_score_gemma":0.000002866,"domain_scores_codex":[0.999367,0.000007018203,0.0001922991,0.0001305154,0.0001231793,0.0001800093],"domain_scores_gemma":[0.9996325,0.00005037795,0.00002122269,0.0001381713,0.00005508387,0.0001026501],"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":[0.00001968174,0.00002855373,3.343449e-7,0.00004928271,0.00002939372,0.000001703782,0.0000559967,0.9979502,0.0001450914,0.0004137971,0.00007391031,0.00123205],"study_design_scores_gemma":[0.0005166285,0.0001034347,2.470794e-7,0.00005078341,0.00005923952,0.000005310715,0.0000909931,0.9966725,0.001746433,0.0002202358,0.0003825179,0.0001516833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004043686,0.0001198848,0.9959997,0.00004644664,0.002727507,0.0002177944,0.00001803845,0.0003704313,0.00009585868],"genre_scores_gemma":[0.8618861,0.00004483653,0.1376521,0.00002146088,0.00008224061,0.00004728691,0.000008964453,0.00005718602,0.0001998398],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8614817,"threshold_uncertainty_score":0.5072973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937638763041735,"score_gpt":0.2605255283083699,"score_spread":0.2311491406779526,"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."}}