{"id":"W2480183620","doi":"10.1109/icc.2016.7511225","title":"Joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Scheduling (production processes); Cellular network; Greedy algorithm; Computer network; Wireless network; Distributed computing; Joint (building); Wireless; Mathematical optimization; 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":[0.0001511735,0.0001066164,0.000119725,0.00005020147,0.0000276905,0.0000155725,0.00002772007,0.00009684051,0.000007393416],"category_scores_gemma":[0.00003131769,0.0000901831,0.00001987315,0.00008350853,0.000006414867,0.0001969257,0.00001172601,0.00004289843,0.000002152486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002651468,"about_ca_system_score_gemma":0.000004004316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004434151,"about_ca_topic_score_gemma":0.00008038119,"domain_scores_codex":[0.9993822,0.00002340052,0.0001872899,0.0001473098,0.00005245439,0.0002073181],"domain_scores_gemma":[0.9996486,0.0001430282,0.00005116077,0.00007897217,0.00004643482,0.00003177165],"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":[0.000009229731,0.000004892448,0.0006353253,0.000006078914,0.00001585724,5.287471e-7,0.00003089216,0.9773484,0.004760192,0.0003220339,0.00005888853,0.01680764],"study_design_scores_gemma":[0.0004898832,0.00002795977,0.0008014617,0.0000430037,0.000007310422,3.210122e-7,0.00001319454,0.9893391,0.008794745,0.0002092507,0.000137973,0.0001357663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1078935,0.0001551536,0.8913246,0.00004409844,0.0001138288,0.0002712194,0.000002498331,0.0001193509,0.00007568657],"genre_scores_gemma":[0.9900905,0.0002363804,0.009189984,0.00002009674,0.00008627476,0.00006354249,0.00001436394,0.00003327228,0.000265556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.882197,"threshold_uncertainty_score":0.367756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008671220193221243,"score_gpt":0.1887101422656559,"score_spread":0.1800389220724347,"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."}}