{"id":"W2344297280","doi":"10.5555/2906831.2907023","title":"Optimal Gaze-Based Robot Selection in Multi-Human Multi-Robot Interaction","year":2016,"lang":"en","type":"article","venue":"Human-Robot Interaction","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Robot; Computer science; Gaze; Artificial intelligence; Human–robot interaction; Selection (genetic algorithm); Computer vision; Population; Robot kinematics; Human–computer interaction; 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":[0.0006559276,0.0003861864,0.0006720643,0.0003492516,0.0006392054,0.0004359573,0.0006673781,0.0004490294,0.001697763],"category_scores_gemma":[0.001411931,0.0003511479,0.0002382944,0.0002302453,0.0007546311,0.0007083717,0.0009579326,0.0003840149,0.0003472172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006204203,"about_ca_system_score_gemma":0.0005821075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003394732,"about_ca_topic_score_gemma":0.004628373,"domain_scores_codex":[0.9995103,0.0001747128,0.00001320239,0.0001311243,0.0001083162,0.00006229665],"domain_scores_gemma":[0.9996599,0.0001473648,0.00005124421,0.00004085393,0.00006346459,0.00003713632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006953071,0.0002978956,0.005127455,0.0001529251,0.0001422328,0.0004381071,0.001661151,0.4716834,0.1586566,0.01716332,0.003163756,0.3408178],"study_design_scores_gemma":[0.00004061829,0.0002228592,0.003774251,0.000008522406,0.00002407605,0.0001618181,0.0001511742,0.9707575,0.01502988,0.008134945,0.0016602,0.00003408153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1252031,0.0004891384,0.8692251,0.0001713731,0.00003010661,0.00006098743,0.00002172816,0.0007027801,0.004095689],"genre_scores_gemma":[0.9146113,0.0001043006,0.08289003,0.00004705707,0.00001515501,0.0000499535,0.00001504605,0.00004445546,0.002222661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003394732,"threshold_uncertainty_score":0.006749928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09996377699074672,"score_gpt":0.3664449657827287,"score_spread":0.266481188791982,"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."}}