{"id":"W4385403839","doi":"10.15607/rss.2023.xix.013","title":"PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection","year":2023,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Korea Advanced Institute of Science and Technology; National Research Foundation of Korea; National Research Foundation","keywords":"Teleoperation; Computer science; Scalability; Robot; Telerobotics; Data collection; Human–computer interaction; Mobile robot; Artificial intelligence; Operating system","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":[0.0008240388,0.0006252984,0.0005288329,0.000444057,0.0004387414,0.0007543776,0.001418388,0.0005228608,0.003805542],"category_scores_gemma":[0.002589982,0.0003218018,0.0002933527,0.0004719226,0.0006625582,0.001442749,0.001524722,0.001079299,0.001302647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004013305,"about_ca_system_score_gemma":0.001088579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001977723,"about_ca_topic_score_gemma":0.002001645,"domain_scores_codex":[0.9992986,0.0001174205,0.00005485059,0.000173776,0.0002734136,0.00008207095],"domain_scores_gemma":[0.9982452,0.0005814746,0.0001867001,0.0005984274,0.0002353321,0.0001528257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001876717,0.0007969097,0.005534853,0.0003658684,0.0001409057,0.0007030326,0.000793185,0.09789556,0.1698045,0.01202354,0.05448005,0.6555849],"study_design_scores_gemma":[0.0001960825,0.0003143707,0.00221321,0.00002331796,0.0000226877,0.0003122674,0.0001585609,0.9077151,0.05609112,0.009882,0.02300332,0.00006804885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02329835,0.0001044423,0.9300717,0.000239316,0.000100419,0.0002166201,0.0003772805,0.04299644,0.002595379],"genre_scores_gemma":[0.5410663,0.0001903206,0.4504029,0.0003307973,0.00009337701,0.0005981576,0.001130108,0.001611693,0.004576362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003805542,"threshold_uncertainty_score":0.01273084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08226045660615232,"score_gpt":0.3365940579349617,"score_spread":0.2543336013288093,"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."}}