{"id":"W2163521536","doi":"10.1109/icc.2007.84","title":"Optimal Scheduling Policy Determination for High Speed Downlink Packet Access","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Granularity; Telecommunications link; Scheduling (production processes); Network packet; Dynamic priority scheduling; Computational complexity theory; Dynamic programming; Mathematical optimization; Heuristic; Bellman equation; Distributed computing; Computer network; Quality of service; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001597232,0.0001447266,0.0001314908,0.0001913856,0.00006551172,0.00006051251,0.0001488587,0.0001064715,0.00003177774],"category_scores_gemma":[0.0000616149,0.0001530847,0.00003834878,0.0003372683,0.00001608659,0.0004989057,0.00002895458,0.00008450262,0.000009282641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001407582,"about_ca_system_score_gemma":0.00001393901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008474159,"about_ca_topic_score_gemma":0.00001830021,"domain_scores_codex":[0.9991333,0.000004497727,0.0002502383,0.0001588422,0.0001042822,0.0003488033],"domain_scores_gemma":[0.9995442,0.0001115195,0.00004126342,0.0001453361,0.00008487148,0.0000727775],"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":[0.00001533111,0.000007366699,0.00008415623,0.00002738178,0.000008013581,0.000001125328,0.00003011775,0.9550397,0.001147984,0.002323184,0.00006502851,0.04125065],"study_design_scores_gemma":[0.0004830226,0.00001997032,0.0007023581,0.00001624881,0.000008276795,0.000002630515,0.00002139543,0.9656671,0.03198262,0.0005995274,0.0002836042,0.0002132683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1295255,0.00002556825,0.8678582,0.0000716017,0.0002282168,0.0002749977,0.000005105943,0.0004705998,0.001540177],"genre_scores_gemma":[0.6863732,0.00002871159,0.3127945,0.000052536,0.0005334139,0.000008221988,0.00006055649,0.00004129369,0.0001075838],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5568476,"threshold_uncertainty_score":0.6242613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505489671929666,"score_gpt":0.2977755658789145,"score_spread":0.2827206691596179,"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."}}