{"id":"W2927741881","doi":"10.1109/hri.2019.8673014","title":"Backseat Teleoperator: Affective Feedback with On-Screen Agents to Influence Teleoperation","year":2019,"lang":"en","type":"article","venue":"","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Teleoperation; Human–computer interaction; Robot; Telerobotics; Computer science; Virtual agent; Perception; Operator (biology); Simulation; Psychology; Artificial intelligence; Mobile robot","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":[0.0004765929,0.0006538701,0.0002080005,0.0001765258,0.0002429281,0.0007626626,0.0004942853,0.0005388925,0.007270373],"category_scores_gemma":[0.002591558,0.0001625615,0.000252605,0.00004351899,0.0003523949,0.0005623316,0.000848956,0.0003883377,0.0006815737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000136223,"about_ca_system_score_gemma":0.0001642915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004294884,"about_ca_topic_score_gemma":0.0005741869,"domain_scores_codex":[0.9996958,0.0001250083,0.00001346217,0.00004954538,0.00007221189,0.0000439667],"domain_scores_gemma":[0.9988151,0.0006381926,0.0001312196,0.0001120334,0.000125587,0.0001779517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002219464,0.002232315,0.0116156,0.0009231175,0.0001231898,0.001165906,0.008012012,0.005292658,0.8493241,0.0024848,0.00235681,0.11425],"study_design_scores_gemma":[0.001345941,0.02816876,0.1413613,0.0005760893,0.001054433,0.003229546,0.009861316,0.1867051,0.522279,0.00739603,0.09753475,0.0004877371],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9173237,0.000140711,0.07123479,0.0002524966,0.0001264514,0.0003568468,0.00007134761,0.001092259,0.009401472],"genre_scores_gemma":[0.9720213,0.00007118088,0.02354332,0.0001852238,0.00002240526,0.0001961317,0.00004801109,0.00008988714,0.003822605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007270373,"threshold_uncertainty_score":0.02432179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734877296769588,"score_gpt":0.3348208374488293,"score_spread":0.3174720644811335,"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."}}