{"id":"W2914253554","doi":"10.1109/iwqos.2018.8624178","title":"Improving Quality of Experience for Mobile Broadcasters in Personalized Live Video Streaming","year":2018,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Quality of experience; Bandwidth (computing); Video quality; Variable bitrate; Real-time computing; Frame (networking); Frame rate; Cellular network; Computer network; Multimedia; Quality of service; Bit rate; Computer vision","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":[0.0007275537,0.0001137172,0.0002316729,0.00008084357,0.00007066083,0.00007671888,0.0005333378,0.00004147269,0.00006568145],"category_scores_gemma":[0.0001714757,0.0001032388,0.00008246049,0.0002073998,0.0001431031,0.000685657,0.0002080362,0.00005187907,0.000007186994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006076981,"about_ca_system_score_gemma":0.0001113002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001706498,"about_ca_topic_score_gemma":0.0001989629,"domain_scores_codex":[0.9985312,0.0001103441,0.0004447163,0.0003884527,0.0002395523,0.000285736],"domain_scores_gemma":[0.9988671,0.0003083401,0.0001745306,0.0004179565,0.0001650234,0.00006708032],"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":[0.0002505395,0.0008150781,0.009818288,0.0005680225,0.00005287083,0.000008151736,0.2339477,0.0000284249,0.2602687,0.07980859,0.0004019063,0.4140317],"study_design_scores_gemma":[0.007284637,0.002948393,0.01650358,0.0003190252,0.0000183817,0.00001118553,0.09296957,0.3294705,0.5422863,0.003855455,0.002720929,0.001612072],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4190418,0.00003566943,0.5799794,0.0000665574,0.0001076265,0.0002880837,0.000002397648,0.00003404597,0.0004443737],"genre_scores_gemma":[0.8957936,0.000001900612,0.1033976,0.0003272546,0.00004077818,0.0001081841,9.743868e-7,0.000004963804,0.0003247531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4767517,"threshold_uncertainty_score":0.4209956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05333419284422682,"score_gpt":0.3778453343869563,"score_spread":0.3245111415427295,"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."}}