{"id":"W2170935086","doi":"10.1109/robot.2007.363975","title":"Performance Issues in Collaborative Haptic Training","year":2007,"lang":"en","type":"article","venue":"Proceedings - IEEE International Conference on Robotics and Automation/Proceedings","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Haptic technology; Trainer; Computer science; Human–computer interaction; Robot; Virtual reality; Simulation; Task (project management); Artificial intelligence; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005088699,0.0002869975,0.000289104,0.0004826831,0.0001206976,0.0004930989,0.0002358466,0.0001422033,0.00005847094],"category_scores_gemma":[0.00006569411,0.0002937592,0.00003252094,0.0003953912,0.00006995967,0.0008201259,0.00002349145,0.0002706605,0.00003864221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000155043,"about_ca_system_score_gemma":0.00003275707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005672789,"about_ca_topic_score_gemma":0.000009054922,"domain_scores_codex":[0.9983246,0.000001400668,0.0005343959,0.0003296774,0.0004561702,0.0003537644],"domain_scores_gemma":[0.9989524,0.00003031604,0.0001342413,0.00003629271,0.0007193559,0.0001274292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000125673,0.0001704976,0.03334812,0.0006353172,0.0002134918,0.000009727932,0.03485874,0.009530389,0.07836565,0.8186324,0.004570364,0.01953966],"study_design_scores_gemma":[0.0007474213,0.0001337947,0.01861242,0.0005366459,0.00001291462,0.00003501701,0.007722589,0.9649028,0.004478875,0.0006467848,0.001671974,0.0004987163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.90222,0.0000418599,0.0005199111,0.001416035,0.0007062662,0.0003098158,0.000006557595,0.0003965134,0.09438302],"genre_scores_gemma":[0.9955415,0.0002229073,0.003239137,0.0001371439,0.0002895701,0.00003616625,0.000006734974,0.00003562901,0.0004911693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9553725,"threshold_uncertainty_score":0.9999515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03714001102228806,"score_gpt":0.2810048740458612,"score_spread":0.2438648630235731,"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."}}