{"id":"W2097746153","doi":"10.1109/glocom.2009.5425897","title":"Stochastic Rate Control for Scalable VBR Video Streaming over Wireless Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Wireless network; Real-time computing; Video quality; Wireless; Computer network; Markov decision process; Greedy algorithm; Channel (broadcasting); Scalability; Markov process; Algorithm","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":[0.0002534712,0.0001673897,0.0002328825,0.00009236224,0.0002189756,0.00023367,0.0009008212,0.0001093918,0.00001015206],"category_scores_gemma":[0.0000741063,0.0001323442,0.00008328943,0.0002354998,0.00003109915,0.00033154,0.0001116134,0.0001383986,0.000009036188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002968094,"about_ca_system_score_gemma":0.00002776099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001242008,"about_ca_topic_score_gemma":0.000002977248,"domain_scores_codex":[0.9987665,0.00003079971,0.0002203696,0.0004094817,0.0001378064,0.0004350328],"domain_scores_gemma":[0.9988777,0.0003210344,0.00008808282,0.0005665619,0.00007600046,0.0000706389],"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":[0.00005153815,0.0001213895,0.000113626,0.00001038894,0.00003176763,0.000007026771,0.00005096328,0.05897653,0.003673874,0.236516,0.01415472,0.6862922],"study_design_scores_gemma":[0.0008669858,0.0001705332,0.0007502216,0.0000510626,0.000007171043,0.00000288539,0.00001585688,0.978022,0.001752946,0.01777941,0.0003786329,0.0002023347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009189192,0.0001736236,0.9870816,0.001508204,0.0002568865,0.0002566605,0.000001191633,0.001067195,0.0004654716],"genre_scores_gemma":[0.989641,0.000007370899,0.008367825,0.001081647,0.00006400405,0.00003901756,8.423455e-7,0.000006916092,0.0007914279],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9804518,"threshold_uncertainty_score":0.5396838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011602793375183,"score_gpt":0.2396390854497346,"score_spread":0.2280362920745516,"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."}}