{"id":"W2482365859","doi":"10.4018/978-1-61520-731-2.ch014","title":"Designing Socially Expressive Character Agents to Facilitate Learning","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Avatar; Character (mathematics); Face (sociological concept); Computer science; Human–computer interaction; Multimedia; Sociology; Social science","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":[0.0008473466,0.000664662,0.00027036,0.000329154,0.0008356535,0.002426563,0.001159553,0.001042295,0.007555678],"category_scores_gemma":[0.002482881,0.0004690183,0.0002723914,0.0002047914,0.001220363,0.002458835,0.002790545,0.001028814,0.002194112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004233876,"about_ca_system_score_gemma":0.0003892011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004630626,"about_ca_topic_score_gemma":0.0008382621,"domain_scores_codex":[0.9993802,0.0002972031,0.00002998154,0.0000851718,0.0001541105,0.00005319353],"domain_scores_gemma":[0.9991546,0.0004407063,0.00006376537,0.0001032144,0.0001160216,0.0001218131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002904168,0.000591389,0.002947909,0.001486346,0.0001019772,0.001164297,0.02070775,0.04764805,0.1104448,0.3466264,0.02259438,0.4453963],"study_design_scores_gemma":[0.0001804394,0.0005345295,0.001553766,0.0003414167,0.00008637233,0.001212643,0.004009547,0.2203225,0.05428838,0.08902065,0.6283104,0.0001393189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04416507,0.0005625593,0.891881,0.0005326789,0.0001938155,0.000526208,0.00006698544,0.0029591,0.0591126],"genre_scores_gemma":[0.3079686,0.0007694205,0.6288413,0.0002441879,0.00005101572,0.001205514,0.0002375686,0.0005509971,0.06013134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007555678,"threshold_uncertainty_score":0.0252763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09059660079495079,"score_gpt":0.3449351231235974,"score_spread":0.2543385223286466,"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."}}