{"id":"W4295093493","doi":"10.3389/fenrg.2022.1002761","title":"Data and model hybrid-driven virtual reality robot operating system","year":2022,"lang":"en","type":"article","venue":"Frontiers in Energy Research","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":5,"is_retracted":true,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Key Research and Development Program of China","keywords":"Teleoperation; Robot; Inverse kinematics; Computer science; Virtual reality; Robot control; Controller (irrigation); Simulation; Human–computer interaction; Artificial intelligence; Control engineering; Mobile robot; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002809153,0.0004422769,0.0005849908,0.0003286641,0.0003818736,0.0008968714,0.001130248,0.0006228437,0.006767395],"category_scores_gemma":[0.0003973227,0.0002351623,0.0005897988,0.0001979666,0.0002859083,0.0006142166,0.000716487,0.0004424578,0.001224296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003439147,"about_ca_system_score_gemma":0.0005617522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00443035,"about_ca_topic_score_gemma":0.002575449,"domain_scores_codex":[0.999757,0.00003675109,0.0000151101,0.00006321463,0.0001056165,0.00002237044],"domain_scores_gemma":[0.9998411,0.00002661287,0.00001799457,0.00003167327,0.00007278063,0.000009714066],"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":[0.0002901774,0.0001168556,0.001373328,0.0002099425,0.00004547132,0.0003605402,0.0001844392,0.8897668,0.02534292,0.01896199,0.004017333,0.05933025],"study_design_scores_gemma":[0.00002253369,0.00007418775,0.0002779234,0.000004294536,0.000009559499,0.00005319539,0.00001483977,0.9916964,0.003493172,0.0009269675,0.003410951,0.00001596283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02836259,0.0001030222,0.9572763,0.0001411974,0.00008688246,0.0001204498,0.0004531239,0.003996321,0.009460117],"genre_scores_gemma":[0.8923813,0.0001804004,0.09404321,0.00007735253,0.00003182727,0.0004130789,0.000998343,0.0001721877,0.01170222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006767395,"threshold_uncertainty_score":0.02263916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207446171448581,"score_gpt":0.361228829602333,"score_spread":0.2404842124574749,"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."}}