{"id":"W2560296492","doi":"10.1109/tro.2016.2623336","title":"A Small-Gain Approach for Nonpassive Bilateral Telerobotic Rehabilitation: Stability Analysis and Controller Synthesis","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Telerobotics; Rehabilitation; Controller (irrigation); Haptic technology; Rehabilitation robotics; Robot; Stability (learning theory); Control engineering; Transparency (behavior); Teleoperation; Computer science; Nonlinear system; Engineering; Simulation; Control (management); Control theory (sociology); Mobile robot; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002379158,0.0002039363,0.0004023341,0.0002393433,0.0001312573,0.00005414375,0.00007887172,0.0001216599,0.00005451749],"category_scores_gemma":[0.00004485218,0.0001506163,0.0002100207,0.0003083159,0.00008137542,0.0001017036,5.571744e-7,0.00008066756,0.000008432187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215782,"about_ca_system_score_gemma":0.00001704171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001060488,"about_ca_topic_score_gemma":0.00008163488,"domain_scores_codex":[0.998879,0.00007582716,0.0003860159,0.0002980054,0.0001263667,0.0002348006],"domain_scores_gemma":[0.9983447,0.00111095,0.00003741698,0.0002696032,0.0001234786,0.0001138588],"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":[0.00004881374,0.0000995556,0.0002012664,0.00009082573,0.0006057769,2.963381e-7,0.0003391669,0.9882299,0.002706322,0.0001563463,0.00003376744,0.007487947],"study_design_scores_gemma":[0.001338134,0.0001584532,0.001023881,0.00003796009,0.0008720132,0.000004301687,0.0003105971,0.9892676,0.006508928,0.00005865132,0.00004768218,0.0003717241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009079119,0.00001665722,0.9890609,0.0005633552,0.0002193328,0.0006465734,0.00008133472,0.0002048706,0.0001278113],"genre_scores_gemma":[0.9419649,0.00001385627,0.05735752,0.00002625097,0.00004005465,0.0003562716,0.000001902718,0.00002655669,0.0002127317],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9328858,"threshold_uncertainty_score":0.6141956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02287719483067786,"score_gpt":0.2110446124666163,"score_spread":0.1881674176359384,"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."}}