{"id":"W2018099115","doi":"10.1177/0278364906068393","title":"Smith Predictor Type Control Architectures for Time Delayed Teleoperation","year":2006,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Teleoperation; Smith predictor; Model predictive control; Control theory (sociology); Controller (irrigation); Artificial neural network; Haptic technology; Nonlinear system; Stability (learning theory); Computer science; Control engineering; Engineering; Control (management); Simulation; PID controller; Artificial intelligence; Machine learning","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":[0.0003103169,0.0003891918,0.0002813366,0.0001884142,0.0002770131,0.0005050256,0.0005718115,0.000499969,0.002854457],"category_scores_gemma":[0.0007215273,0.0001862332,0.0001662577,0.0002758679,0.0004222689,0.0006167996,0.0003353092,0.0008419849,0.0003900814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003987456,"about_ca_system_score_gemma":0.0005964965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00211108,"about_ca_topic_score_gemma":0.002682463,"domain_scores_codex":[0.9998511,0.00002536597,0.00001062417,0.00003069564,0.00006692176,0.0000152851],"domain_scores_gemma":[0.9997301,0.00009702853,0.00003485939,0.00003331608,0.00009335843,0.00001137935],"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":[0.0002968949,0.00009401567,0.0008401467,0.0002254272,0.00005678769,0.0001661901,0.0001970654,0.6065393,0.05019759,0.04188828,0.00215376,0.2973445],"study_design_scores_gemma":[0.00002285125,0.0001636343,0.0002340872,0.00001270888,0.00001411578,0.00004398385,0.00001077701,0.9787223,0.01118859,0.005800479,0.003773173,0.00001340668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01796297,0.0004325103,0.9762321,0.0001372502,0.0001188935,0.00003637837,0.00002687909,0.0008554574,0.004197638],"genre_scores_gemma":[0.8517143,0.0008836965,0.1345721,0.000119014,0.00008129004,0.0001218644,0.0000708712,0.00003662534,0.01240026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002854457,"threshold_uncertainty_score":0.009549141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02461945157399061,"score_gpt":0.3060376033847289,"score_spread":0.2814181518107383,"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."}}