{"id":"W2108881220","doi":"10.1109/acc.2009.5160311","title":"Bilateral teleoperation using unknown input observers for force estimation","year":2009,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Teleoperation; Computer science; Control theory (sociology); Controller (irrigation); Telerobotics; Haptic technology; Stability (learning theory); State (computer science); Mode (computer interface); Work (physics); Measure (data warehouse); Control engineering; Simulation; Control (management); Robot; Engineering; Artificial intelligence; Mobile robot; Algorithm; Human–computer interaction","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":[0.0007148703,0.0004679974,0.0003799309,0.0002068056,0.000219876,0.0005345321,0.0004970396,0.0006894811,0.001093381],"category_scores_gemma":[0.002265441,0.0001522085,0.0002372613,0.0001747951,0.0004794851,0.0009955373,0.0007079729,0.0007835635,0.000134281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666354,"about_ca_system_score_gemma":0.0003871876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009473753,"about_ca_topic_score_gemma":0.0009164599,"domain_scores_codex":[0.9995491,0.0001140379,0.00002324004,0.00005827937,0.0002270629,0.00002827049],"domain_scores_gemma":[0.9992099,0.000396047,0.0001226148,0.0001124243,0.000140403,0.00001858764],"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":[0.0003555233,0.0002107117,0.001582987,0.0003424336,0.00007261429,0.0003190999,0.00065014,0.4173843,0.1167738,0.06626655,0.001335325,0.3947065],"study_design_scores_gemma":[0.00002407732,0.0001073577,0.0002477404,0.000009229926,0.00001090474,0.00003996013,0.00001516077,0.9878127,0.006692619,0.003962104,0.001067354,0.00001074256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01015847,0.000168014,0.9885062,0.00007000312,0.00002802407,0.00001300124,0.000003293889,0.0001088724,0.0009440804],"genre_scores_gemma":[0.8720381,0.0003486669,0.1253241,0.00003843499,0.00006627601,0.0001026121,0.00001539294,0.00001622371,0.002050194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001093381,"threshold_uncertainty_score":0.003780603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02548783270213522,"score_gpt":0.252838606484923,"score_spread":0.2273507737827877,"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."}}