{"id":"W4416202460","doi":"10.1109/toh.2025.3632157","title":"Inertia Compensation Using Flywheels in Parallel Robots for the Assisted Manipulation of Large Payloads","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Haptics","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flywheel; Compensation (psychology); Robot; Control theory (sociology); Torque; Inertia; Payload (computing); Actuator; Rendering (computer graphics)","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":[0.0001528964,0.0001022755,0.0001529956,0.0001642851,0.0000932637,0.00002350501,0.00007160426,0.000085278,0.00001536737],"category_scores_gemma":[0.000005558333,0.0000891236,0.00006420006,0.0002484689,0.0000152989,0.00007485637,4.45943e-7,0.0001034537,0.000002927057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008886479,"about_ca_system_score_gemma":0.00002138845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004509154,"about_ca_topic_score_gemma":0.0004641088,"domain_scores_codex":[0.9992983,0.00002521712,0.0003552821,0.00009559505,0.00009726427,0.0001283535],"domain_scores_gemma":[0.9995609,0.0001536005,0.0000344544,0.0001706814,0.00006365141,0.0000167131],"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":[0.0000192188,0.0000528815,0.00007305523,0.00007087514,0.00004962971,1.910855e-7,0.0002166084,0.9843641,0.01047812,0.001660115,0.00003708585,0.002978119],"study_design_scores_gemma":[0.00077582,0.00001673566,0.002940017,0.00006481928,0.00005424405,0.000001315957,0.000130383,0.9910659,0.00445509,0.00003936444,0.0003711027,0.00008521257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03693284,0.00006235193,0.9613879,0.0001241333,0.0007602695,0.0004423944,0.00001815659,0.00006992625,0.0002019994],"genre_scores_gemma":[0.996397,0.00001836576,0.003275572,0.00005207624,0.00001956283,0.00004565455,0.000005116602,0.00001507901,0.0001716161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9594641,"threshold_uncertainty_score":0.3634355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04640454304057548,"score_gpt":0.2916611835341837,"score_spread":0.2452566404936083,"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."}}