{"id":"W2728472544","doi":"10.1609/aiide.v11i1.12800","title":"A Lightweight Algorithm for Procedural Generation of Emotionally Affected Behavior and Appearance","year":2015,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Scripting language; Computer science; Character (mathematics); Testbed; Virtual actor; Fidelity; Human–computer interaction; Component (thermodynamics); Scope (computer science); Virtual reality; Baseline (sea); Artificial intelligence; World Wide Web; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.0001232426,0.0001736889,0.0002300236,0.00008791213,0.00007201894,0.0001281665,0.000165093,0.00006872738,0.0000462663],"category_scores_gemma":[0.0001720164,0.0001323123,0.00009082011,0.000103878,0.0001955739,0.0003960636,0.00006993424,0.0001296443,0.00001016426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005205845,"about_ca_system_score_gemma":0.00003328705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000217894,"about_ca_topic_score_gemma":0.000004667595,"domain_scores_codex":[0.9988813,0.00001186241,0.00040068,0.0003081975,0.0002252149,0.0001727539],"domain_scores_gemma":[0.9987777,0.000045763,0.0003387778,0.0000711991,0.0006795473,0.00008703949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001545904,0.002509258,0.002313249,0.00009157187,0.0002891418,0.00000106237,0.02142372,0.00000437358,0.04487022,0.2269049,0.001774624,0.6982719],"study_design_scores_gemma":[0.001503397,0.008351455,0.01305305,0.001667418,0.0002930021,0.00009585655,0.07009386,0.03762986,0.8323568,0.03156396,0.002112175,0.001279221],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848029,0.00004713853,0.005401619,0.001221721,0.0007436882,0.001122282,0.00006729735,0.00002302991,0.006570342],"genre_scores_gemma":[0.9986727,0.000009738351,0.0002000823,0.0001692663,0.00009881404,0.0001651486,0.000007223644,0.00001253232,0.0006645585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7874865,"threshold_uncertainty_score":0.5395539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184930455239885,"score_gpt":0.3571515260730677,"score_spread":0.2386584805490791,"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."}}