{"id":"W2167353611","doi":"10.1109/iros.2009.5354183","title":"Experimental performance evaluation of a haptic training simulation system","year":2009,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Haptic technology; Computer science; Trainer; Task (project management); Robot; Simulation; Virtual machine; Architecture; Human–computer interaction; Trajectory; Point (geometry); Virtual reality; Control (management); Artificial intelligence; Engineering; Operating system; Systems engineering","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":[0.0002532377,0.00005719562,0.00008976208,0.00004839774,0.00002204655,0.00001175047,0.00003006297,0.00002812647,0.00008020569],"category_scores_gemma":[0.000005718845,0.00005357867,0.00001915195,0.00006089625,0.000004002471,0.0001160365,0.000001256915,0.00002124389,0.00001950735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008289188,"about_ca_system_score_gemma":0.00001138305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000153382,"about_ca_topic_score_gemma":4.670719e-7,"domain_scores_codex":[0.9994335,0.00001655648,0.0001927627,0.0000563969,0.0002305783,0.00007020398],"domain_scores_gemma":[0.9998147,0.000009923099,0.00001877512,0.0000786922,0.00005652109,0.00002141001],"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":[0.000002170498,0.000007502263,0.0000280476,0.00001829867,0.000006625698,7.550986e-8,0.002024486,0.9386387,0.03846415,0.001017862,0.00001133636,0.01978079],"study_design_scores_gemma":[0.0003158891,0.000040164,0.001726388,0.00003851938,0.000008326299,0.00000255595,0.001663389,0.9810177,0.01510056,0.00000102562,0.00002683668,0.00005861402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9501838,0.0001263617,0.009609103,0.000003422577,0.000159367,0.0001817473,3.217771e-7,0.0002003326,0.03953554],"genre_scores_gemma":[0.9996275,3.784048e-7,0.0002707535,0.000006649565,0.00004756654,0.000008235651,0.000002442278,0.000005639991,0.00003078665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04944374,"threshold_uncertainty_score":0.2184875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06011480657900461,"score_gpt":0.2878430451476868,"score_spread":0.2277282385686822,"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."}}