{"id":"W6926371595","doi":"10.20380/gi2022.23","title":"It's Over There: Designing an Intelligent Virtual Agent That Can Point Accurately into the Real World","year":2022,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of British Columbia","funders":"","keywords":"Situated; Point (geometry); Perception; Dimension (graph theory); Gesture; Virtual world; Virtual reality","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0006065278,0.0002810008,0.0002255792,0.00006656979,0.003824496,0.0003493899,0.006229667,0.00003483175,0.0001573326],"category_scores_gemma":[0.000005893213,0.0002488357,0.0002331765,0.0005544852,0.0001871277,0.0005192508,0.003680383,0.0008762891,0.000004465853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001717688,"about_ca_system_score_gemma":0.0008937872,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.242761,"about_ca_topic_score_gemma":0.4930026,"domain_scores_codex":[0.9973252,0.0007607669,0.0003872266,0.0004975699,0.0005865909,0.0004426214],"domain_scores_gemma":[0.9958601,0.0004261116,0.0002661172,0.003115968,0.000177167,0.0001545334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000179669,0.0006406304,0.001509753,0.00001866371,0.0007627319,0.00003478736,0.2341786,0.006230562,0.004002614,0.211962,0.5245214,0.0161203],"study_design_scores_gemma":[0.001122155,0.0005834058,0.0256077,0.00008390834,0.000112336,0.00003954755,0.06208891,0.3070315,0.005500662,0.003064483,0.592794,0.001971425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1507707,0.001282817,0.7428648,0.08610044,0.004382591,0.002496655,0.0001162932,0.0003405276,0.01164508],"genre_scores_gemma":[0.9692943,0.00008750844,0.01064377,0.01890724,0.00009285557,0.0001654071,0.000119611,0.00002864309,0.000660682],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8185236,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08054107852547202,"score_gpt":0.3209097898592336,"score_spread":0.2403687113337616,"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."}}