{"id":"W2060598493","doi":"10.1109/vetecf.2008.419","title":"Optimal Linear-Time Algorithm for Uplink Scheduling of Packets with Hard or Soft Deadlines in WiMAX","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada); Queen's University","funders":"","keywords":"Computer science; Telecommunications link; Network packet; Scheduling (production processes); WiMAX; Quality of service; Mathematical optimization; Distributed computing; Algorithm; Computer network; Wireless; Mathematics","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":[0.002349782,0.001041461,0.001247253,0.0005558282,0.0005678873,0.001217929,0.001577179,0.001195311,0.002966371],"category_scores_gemma":[0.005028882,0.0005616423,0.0004778277,0.0008346324,0.001218588,0.001447851,0.001099076,0.00141112,0.0005440927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002601998,"about_ca_system_score_gemma":0.00367228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005871692,"about_ca_topic_score_gemma":0.006702565,"domain_scores_codex":[0.9986711,0.0005839448,0.00005107321,0.0001891688,0.0002526309,0.0002521915],"domain_scores_gemma":[0.9981046,0.001304849,0.000229898,0.0001030342,0.0001757995,0.00008174805],"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":[0.0001374164,0.0000924593,0.0001937019,0.00008440936,0.00002196476,0.00002538154,0.00007147877,0.9480668,0.001145139,0.02328177,0.001197416,0.02568193],"study_design_scores_gemma":[0.00003223566,0.00002966461,0.00002697609,0.000003145934,0.000004007026,0.000006731845,0.000008872655,0.9931358,0.0002572713,0.006295457,0.0001959484,0.000003798131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01322372,0.0002196416,0.983576,0.0002341829,0.00003196567,0.00006882292,0.0000473621,0.0003712454,0.002227033],"genre_scores_gemma":[0.5038353,0.0003370316,0.4910085,0.0002411051,0.00006297514,0.0003804291,0.0002227721,0.0001705493,0.003741296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005871692,"threshold_uncertainty_score":0.01887888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01598133634795148,"score_gpt":0.2291129184258459,"score_spread":0.2131315820778944,"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."}}