{"id":"W6967244403","doi":"10.48550/arxiv.2508.05143","title":"From Canada to Japan: How 10,000 km Affect User Perception in Robot Teleoperation","year":2025,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Teleoperation; Robot; Perception; Robotics; Telerobotics; Software; Affect (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000772836,0.0002473701,0.0002033643,0.0003678357,0.001682562,0.00161677,0.0002701011,0.0004518754,0.002662232],"category_scores_gemma":[0.005395112,0.0001229226,0.0002001176,0.0004482175,0.001015721,0.0003893582,0.000799627,0.000421835,0.000182283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003862578,"about_ca_system_score_gemma":0.004019667,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7657668,"about_ca_topic_score_gemma":0.8218638,"domain_scores_codex":[0.9993999,0.0001672716,0.00002238105,0.0000777208,0.0001893011,0.0001433949],"domain_scores_gemma":[0.9961647,0.001291287,0.0004217027,0.0001109161,0.001226853,0.0007846294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001543326,0.000365418,0.7869003,0.0001864292,0.00009643399,0.0006717737,0.1597316,0.0004911897,0.01461425,0.0003617065,0.001998186,0.0330394],"study_design_scores_gemma":[0.000008698085,0.0001541584,0.9249406,0.0000239701,0.00002486088,0.00004037626,0.07243833,0.0003326489,0.000512913,0.00005038712,0.001434343,0.00003876298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977636,0.00006182375,0.00007794607,0.00006321505,0.00000575214,0.000008149673,0.00003718555,0.000004176959,0.00197818],"genre_scores_gemma":[0.9986693,0.00006913529,0.00009381206,0.00005123919,0.000001942373,0.000007026665,0.00003838396,0.000005336675,0.001063961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2342332,"threshold_uncertainty_score":0.4712253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07213140386275743,"score_gpt":0.2510447672123116,"score_spread":0.1789133633495541,"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."}}