{"id":"W2124977877","doi":"10.1109/wpmc.2002.1088350","title":"Scheduling of multimedia traffic in interference-limited broadband wireless access networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer network; Wireless broadband; Broadband networks; Quality of service; Base station; Network packet; Scheduling (production processes); Broadband; Packet loss; Wireless network; Wireless; Transmission delay; Real-time computing; Telecommunications; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007142329,0.0004888843,0.0004254139,0.000416403,0.000538338,0.000431571,0.0006789099,0.0003762776,0.0006599771],"category_scores_gemma":[0.002059353,0.0002389291,0.0001677053,0.0004922872,0.0004604718,0.0004731576,0.0002888492,0.000255396,0.000127702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007983293,"about_ca_system_score_gemma":0.0006526199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001588422,"about_ca_topic_score_gemma":0.00179321,"domain_scores_codex":[0.9996835,0.0001351889,0.00001281982,0.00003136985,0.00009350815,0.00004354899],"domain_scores_gemma":[0.9993068,0.0004321109,0.0001065466,0.00002864367,0.00008187049,0.00004406883],"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":[0.0002230947,0.0001255434,0.0009316753,0.00008666235,0.00002579358,0.0001183452,0.00007346071,0.9044902,0.01404398,0.01184192,0.0009337958,0.06710555],"study_design_scores_gemma":[0.00001081974,0.00005175369,0.0001316529,0.000002278622,0.00000516097,0.00001917672,0.000008049203,0.9960872,0.001498617,0.00186017,0.0003227264,0.000002353821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1686423,0.0005689007,0.826185,0.0002022489,0.00006716861,0.00008195169,0.00004355262,0.0002580342,0.003950939],"genre_scores_gemma":[0.8986896,0.0003363983,0.0994993,0.00005459338,0.00008989139,0.0000782017,0.00005707462,0.00003957057,0.001155331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001588422,"threshold_uncertainty_score":0.00579232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418768945820969,"score_gpt":0.2394261208312793,"score_spread":0.2252384313730696,"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."}}