{"id":"W4298140738","doi":"10.24846/v31i3y202204","title":"An Improved Composite State Convergence Scheme with Disturbance Compensation for Multilateral Teleoperation Systems","year":2022,"lang":"en","type":"article","venue":"Studies in Informatics and Control","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Teleoperation; Computer science; Convergence (economics); Scheme (mathematics); Compensation (psychology); Disturbance (geology); Composite number; Control theory (sociology); State (computer science); Artificial intelligence; Algorithm; Robot; Mathematics; Geology; Control (management)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008196583,0.0003914148,0.0004550057,0.0002983174,0.0003678758,0.000535426,0.0007715064,0.0004643146,0.00160778],"category_scores_gemma":[0.0009626546,0.0001655441,0.0003389117,0.0002808068,0.0006243328,0.0009703573,0.00109888,0.0009463856,0.0003292142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003060782,"about_ca_system_score_gemma":0.0004113341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001066265,"about_ca_topic_score_gemma":0.000801139,"domain_scores_codex":[0.9995723,0.000118266,0.00003178578,0.00006482529,0.0001769228,0.00003583815],"domain_scores_gemma":[0.999564,0.0001102494,0.00005102498,0.00008433956,0.0001572299,0.00003316281],"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":[0.0004976035,0.0001150942,0.0006001014,0.0002106551,0.00005226169,0.0002547064,0.0006851056,0.569128,0.07922763,0.1002006,0.001543629,0.2474847],"study_design_scores_gemma":[0.00002082673,0.0001526207,0.0001087733,0.000005913177,0.000004715691,0.00003707778,0.00001076322,0.9871825,0.00641204,0.003945946,0.002104555,0.00001417602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008570142,0.00005619348,0.9899986,0.00002785216,0.00002872133,0.00001826431,0.000005485562,0.0001595734,0.001135165],"genre_scores_gemma":[0.817539,0.0001423573,0.1780377,0.00003741317,0.00003522924,0.00009516795,0.00004566482,0.00004136768,0.004026015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00160778,"threshold_uncertainty_score":0.005378544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118261404019885,"score_gpt":0.2389541634288882,"score_spread":0.2271280230268997,"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."}}