{"id":"W3048981493","doi":"10.1609/aiide.v16i1.7408","title":"Computer-Generated Music for Tabletop Role-Playing Games","year":2020,"lang":"en","type":"preprint","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Music and Audio Processing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Musical; Speech recognition; Human–computer interaction; Artificial intelligence; Visual arts; Art","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001984498,0.0005365927,0.0006146167,0.0001496981,0.0002444508,0.002105194,0.001764412,0.0001607185,0.00001913534],"category_scores_gemma":[0.0001951831,0.0004138556,0.0002794279,0.0002392105,0.0002148178,0.000956026,0.002267273,0.0006081226,0.00001314177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139712,"about_ca_system_score_gemma":0.0001509851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001788142,"about_ca_topic_score_gemma":0.000001668295,"domain_scores_codex":[0.9971525,0.00001541282,0.0008021493,0.001122003,0.0004659394,0.0004419797],"domain_scores_gemma":[0.9978088,0.0001393006,0.0008930477,0.0002870421,0.0007116977,0.0001601027],"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":[0.0004089418,0.0005464972,0.0001812086,0.000685594,0.000305765,0.000002360287,0.01001003,0.0003272523,0.03204721,0.2245274,0.001368951,0.7295888],"study_design_scores_gemma":[0.0001124058,0.0007044463,0.00006031935,0.002263187,0.00005101848,0.000008178865,0.001720563,0.5590397,0.3020839,0.1322484,0.000981904,0.0007260082],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2420398,0.000156072,0.7307042,0.01191136,0.00229096,0.002509601,0.0001809463,0.0002333107,0.009973662],"genre_scores_gemma":[0.9946043,0.00003799939,0.00347911,0.001327521,0.0002450163,0.0001381714,0.00001418257,0.00002740184,0.0001262457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7525645,"threshold_uncertainty_score":0.9998313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07577476007535631,"score_gpt":0.2865265553895373,"score_spread":0.2107517953141809,"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."}}