{"id":"W2118405462","doi":"10.1109/robot.2005.1570267","title":"Design of Bilateral Teleoperators for Soft Environments with Adaptive Environmental Impedance Estimation","year":2006,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Algonquin College; University of Waterloo; Carleton University","funders":"","keywords":"Fidelity; Stability (learning theory); Constraint (computer-aided design); Measure (data warehouse); Mathematical optimization; Control theory (sociology); High fidelity; Engineering; Electrical impedance; Scheme (mathematics); Computer science; Control engineering; Mathematics; Artificial intelligence; Data mining; Machine learning; Control (management); Telecommunications","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":[0.0009999793,0.0006268403,0.0005136795,0.0002110877,0.0003536663,0.0005823683,0.0009578938,0.0009527131,0.001528082],"category_scores_gemma":[0.00369786,0.0003113585,0.0003729216,0.0001207731,0.0006495818,0.001260269,0.002010122,0.000859737,0.0002522752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002606681,"about_ca_system_score_gemma":0.0004265395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003675053,"about_ca_topic_score_gemma":0.0003772772,"domain_scores_codex":[0.9992519,0.0001851907,0.00003348009,0.0001616948,0.0002833227,0.00008444407],"domain_scores_gemma":[0.9985261,0.0006038568,0.0003623559,0.0001624317,0.0002261035,0.0001191776],"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":[0.0003645145,0.0001708803,0.001709975,0.0003228441,0.00006783865,0.0003338387,0.0006631351,0.6363373,0.1327527,0.02519783,0.0006982374,0.2013808],"study_design_scores_gemma":[0.0000534409,0.0003707447,0.0004496404,0.00001927965,0.0000145121,0.0001371367,0.00006845274,0.9793591,0.01211455,0.005189725,0.002202095,0.00002126821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0157717,0.00004641317,0.9835082,0.00004890772,0.000009836144,0.00002546649,0.000004929198,0.00004954452,0.0005349729],"genre_scores_gemma":[0.7887612,0.0001174215,0.2091447,0.00006045877,0.00002658736,0.0002002943,0.00002224274,0.00003494469,0.001632109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001528082,"threshold_uncertainty_score":0.005288422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00720751685479864,"score_gpt":0.1712703953783209,"score_spread":0.1640628785235223,"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."}}