{"id":"W2958997194","doi":"10.1109/icc.2019.8761510","title":"QoE-Oriented Resource Optimization for Mobile Cloud Gaming: A Potential Game Approach","year":2019,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Cloud computing; Computer science; Provisioning; Server; Quality of service; Quality of experience; The Internet; Rendering (computer graphics); Game theory; Resource (disambiguation); Distributed computing; Multimedia; Computer network; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003864653,0.000171135,0.0001880508,0.0001269702,0.0001193586,0.0001726247,0.0007431036,0.00007220866,0.0000309086],"category_scores_gemma":[0.00001457805,0.0001474425,0.0001337137,0.0003906978,0.00002273426,0.00003698143,0.0004982447,0.00009616187,0.00004215204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004395216,"about_ca_system_score_gemma":0.00002037165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009704004,"about_ca_topic_score_gemma":1.36386e-7,"domain_scores_codex":[0.9983513,0.00005660013,0.0002616308,0.0006263535,0.0003181498,0.0003859793],"domain_scores_gemma":[0.9989482,0.00005631333,0.0001097085,0.0007188182,0.00007899982,0.00008793264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001477432,0.0001276559,0.00002788754,0.00004027279,0.00002359664,0.00000119892,0.0004600898,0.9771917,0.00004633889,0.01128016,0.002622274,0.008164089],"study_design_scores_gemma":[0.0007450568,0.0001719184,0.00002439253,0.00001229014,0.000009394356,0.000007245641,0.0002392561,0.943771,0.00009722623,0.0000720711,0.0546483,0.0002018449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06039292,0.00004327111,0.9239523,0.0001986223,0.0005128204,0.0009093694,8.72521e-7,0.0004235243,0.01356624],"genre_scores_gemma":[0.697089,0.000001326834,0.2846258,0.0004790866,0.0003390808,0.00009642757,0.00002050463,0.00002800632,0.01732068],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6393265,"threshold_uncertainty_score":0.6012529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00666167137791899,"score_gpt":0.2085034262222326,"score_spread":0.2018417548443136,"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."}}