{"id":"W4306681012","doi":"10.1609/aiide.v18i1.21972","title":"EM-Glue: A Platform for Decoupling Experience Managers and Environments","year":2022,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Rannís","keywords":"Decoupling (probability); Computer science; Software; Human–computer interaction; Visualization; Field (mathematics); Software engineering; Engineering; Operating system; Artificial intelligence","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":[0.002008244,0.0009293703,0.0004390012,0.0007590916,0.0006780616,0.002678005,0.002426119,0.001194704,0.01314001],"category_scores_gemma":[0.006336369,0.0008677656,0.0007120967,0.0003385575,0.0007801433,0.005548059,0.008140286,0.002556853,0.005462509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005393385,"about_ca_system_score_gemma":0.00120418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009525547,"about_ca_topic_score_gemma":0.001449134,"domain_scores_codex":[0.9990226,0.000241979,0.0001091665,0.0002060207,0.0002405116,0.0001795815],"domain_scores_gemma":[0.9976713,0.0005102381,0.0001621349,0.0008213278,0.0002218178,0.0006131863],"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":[0.004912954,0.001745629,0.01081833,0.001150874,0.0002864511,0.002958882,0.007209028,0.01739432,0.09385559,0.1917675,0.1349404,0.5329602],"study_design_scores_gemma":[0.0008581192,0.001203984,0.007337618,0.0004277426,0.0001908013,0.001472264,0.001295081,0.1527282,0.07212429,0.08574699,0.6762182,0.0003967262],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02828614,0.0001672243,0.869276,0.0006438061,0.0002802527,0.0005327291,0.0007508187,0.0786332,0.02142987],"genre_scores_gemma":[0.3527256,0.0003981856,0.5782444,0.001141462,0.0002249874,0.001204514,0.003720645,0.01046138,0.05187887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01314001,"threshold_uncertainty_score":0.04395777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05359777811706851,"score_gpt":0.3056671953468355,"score_spread":0.2520694172297669,"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."}}