{"id":"W1559991383","doi":"","title":"Close Reading Oblivion: Character Believability and Intelligent Personalization in Games","year":2009,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Character (mathematics); Reading (process); Computer science; Context (archaeology); Personalization; Class (philosophy); Artificial intelligence; Human–computer interaction; World Wide Web; Linguistics; History","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":[0.001929405,0.000441699,0.0002458624,0.0007769261,0.001292296,0.003908828,0.0008928253,0.001046841,0.002482298],"category_scores_gemma":[0.01090561,0.000324161,0.0004027837,0.0003230386,0.007585927,0.006822598,0.003271207,0.002014385,0.0002299676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00132972,"about_ca_system_score_gemma":0.0003707841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121118,"about_ca_topic_score_gemma":0.000954357,"domain_scores_codex":[0.9969469,0.001981412,0.00008817309,0.0003944106,0.0003431182,0.0002460375],"domain_scores_gemma":[0.9945977,0.002966079,0.0007049998,0.00100689,0.0003661868,0.0003581808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005328159,0.0002887772,0.02686401,0.0002123352,0.00008452694,0.001125727,0.3162968,0.005755986,0.009774473,0.5310072,0.001515608,0.1065417],"study_design_scores_gemma":[0.00009352896,0.0007709563,0.05763031,0.0002273989,0.0001246195,0.002853155,0.1001093,0.051559,0.01520547,0.7115832,0.0596105,0.0002325878],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7302049,0.0004659761,0.1572514,0.002095708,0.00004782415,0.00011152,0.00003036321,0.0002537618,0.1095386],"genre_scores_gemma":[0.9919733,0.0000376048,0.00546211,0.0000462956,0.000007848122,0.00001603355,0.00001181748,0.00002435239,0.002420759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003908828,"threshold_uncertainty_score":0.01020378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692474316830172,"score_gpt":0.2916062239466866,"score_spread":0.2646814807783848,"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."}}