{"id":"W2067141342","doi":"10.1109/iros.2013.6696344","title":"&amp;#x201C;You two! Take off!&amp;#x201D;: Creating, modifying and commanding groups of robots using face engagement and indirect speech in voice commands","year":2013,"lang":"en","type":"article","venue":"","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Face (sociological concept); Computer science; Speech recognition; Robot; Artificial intelligence; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007784624,0.0005453764,0.0003082616,0.000263557,0.0006406835,0.0008364422,0.001012143,0.0008749186,0.0316417],"category_scores_gemma":[0.002537678,0.0001750078,0.0002518323,0.0001392016,0.0008400877,0.0009781544,0.001489903,0.0004739392,0.009262992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002178406,"about_ca_system_score_gemma":0.0002461979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000950942,"about_ca_topic_score_gemma":0.002003813,"domain_scores_codex":[0.9995775,0.0001457961,0.00001637981,0.00008366241,0.0001202585,0.00005647961],"domain_scores_gemma":[0.998949,0.0004432335,0.00006486808,0.000224567,0.0001402063,0.0001781697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001102505,0.0005471535,0.003782063,0.0003423121,0.000058302,0.0006342042,0.003226939,0.004817392,0.1483926,0.008633082,0.05684852,0.771615],"study_design_scores_gemma":[0.0005507196,0.00415421,0.02488812,0.0002423314,0.0001742346,0.002458841,0.003726392,0.3435928,0.2389544,0.01865749,0.3621982,0.0004022832],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1666824,0.0003535086,0.7185012,0.00126905,0.0005080077,0.0007011542,0.000513247,0.02927981,0.0821917],"genre_scores_gemma":[0.5844813,0.0001973618,0.337615,0.0007689212,0.0001876794,0.0008964412,0.0006311451,0.001036511,0.0741857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0316417,"threshold_uncertainty_score":0.105852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.156621401134641,"score_gpt":0.4001188607591431,"score_spread":0.2434974596245021,"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."}}