{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001036514,0.0002860428,0.0003566085,0.0003212167,0.0001060082,0.00007459394,0.0004014393,0.0004323557,0.006700405],"category_scores_gemma":[0.00005910569,0.0003666517,0.0001325139,0.0004216794,0.00002765861,0.0001196187,0.0002458246,0.0006393866,0.0003251416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001253323,"about_ca_system_score_gemma":0.0003600414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7923122,"about_ca_topic_score_gemma":0.8283316,"domain_scores_codex":[0.9982318,0.0003187756,0.0001725642,0.0008918448,0.00008607064,0.0002989808],"domain_scores_gemma":[0.9989018,0.0001589692,0.0001167336,0.0005596539,0.0001233988,0.0001394321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00199757,0.0008076052,0.1904858,0.0001461662,0.001059887,0.0008165308,0.01732147,0.358106,0.001107776,0.0175443,0.4027426,0.007864307],"study_design_scores_gemma":[0.002325821,0.0001556172,0.9111591,0.0004447801,0.0003004113,0.000002495141,0.01922186,0.006481229,0.000106064,0.0008872902,0.05737977,0.001535556],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9676328,0.00001583026,0.003814536,0.001100485,0.003767352,0.000556213,0.0001870271,0.00008901885,0.02283673],"genre_scores_gemma":[0.9230589,0.00001706037,0.00005716085,0.0006788397,0.0002921772,0.000006820456,0.0002221874,0.00001496798,0.07565192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7206733,"threshold_uncertainty_score":0.9998785,"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."}}