{"id":"W2113958730","doi":"10.1109/glocom.2008.ecp.288","title":"A Simple, Two-Level Markovian Traffic Model for IPTV Video Sources","year":2008,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"IPTV; Computer science; Real-time computing; Markov process; Markov chain; Queue; Frame (networking); Computer network; Variable bitrate; Group of pictures; Algorithm; Bit rate; Decoding methods; Statistics","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":[0.0002015067,0.0001873306,0.0002189704,0.00007965507,0.0003144703,0.00008849052,0.0007628612,0.00006356509,0.000031207],"category_scores_gemma":[0.00002230473,0.0001620072,0.0001509017,0.0002181181,0.00006086718,0.0003364602,0.0000795069,0.00009536576,0.0000438833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002306056,"about_ca_system_score_gemma":0.0001495624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008755665,"about_ca_topic_score_gemma":0.00008709884,"domain_scores_codex":[0.9985548,0.00003170874,0.0002675788,0.0004625624,0.0002338302,0.0004495413],"domain_scores_gemma":[0.9990162,0.0001923245,0.00006693691,0.0004479208,0.0001038816,0.0001727759],"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":[0.00004103139,0.0001051812,0.0001115412,0.000008540565,0.00003943167,0.00001221522,0.0008057384,0.3947988,0.00003171535,0.05701947,0.0306551,0.5163712],"study_design_scores_gemma":[0.001180619,0.00005368618,0.0001535197,0.000004238413,0.000007750968,0.00002780108,0.00001460976,0.9924828,0.00001770253,0.001240059,0.00458504,0.0002321178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03278064,0.0001088152,0.9629179,0.00140225,0.0001532919,0.0003234521,0.000006528474,0.0004834128,0.001823712],"genre_scores_gemma":[0.9055552,0.00001290865,0.08410675,0.001789044,0.0001717341,0.00008840417,0.000003918165,0.00001415218,0.008257892],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8788111,"threshold_uncertainty_score":0.660646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100074172206641,"score_gpt":0.2475681259144796,"score_spread":0.2065673841924132,"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."}}