{"id":"W2160876140","doi":"10.1109/glocom.2008.ecp.452","title":"Channel and Delay Margin Aware Bandwidth Allocation for Future Generation Wireless Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Queuing delay; Queueing theory; Telecommunications link; Network packet; Bandwidth (computing); Queue; Base station; Channel (broadcasting); Bandwidth allocation; Wireless; Wireless network; Channel allocation schemes; 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":[0.0009952153,0.0004401116,0.0004600155,0.000372603,0.0002981164,0.0007546745,0.0005003976,0.0005288702,0.001202386],"category_scores_gemma":[0.00183374,0.0002367935,0.0001693299,0.000498615,0.0005206309,0.001133572,0.0004123751,0.0004526862,0.0001156385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009218051,"about_ca_system_score_gemma":0.0007539166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002137741,"about_ca_topic_score_gemma":0.002197445,"domain_scores_codex":[0.9997265,0.0001096392,0.000006800096,0.00003891158,0.0000628585,0.00005537676],"domain_scores_gemma":[0.9993773,0.0003895719,0.00009071636,0.0000327062,0.00007451706,0.00003535318],"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":[0.00006213369,0.00001791677,0.0003219283,0.00004546604,0.00001703342,0.00003365349,0.00002350647,0.9487079,0.002578815,0.0245282,0.0007798199,0.02288365],"study_design_scores_gemma":[0.000004656487,0.00001721386,0.0001470685,0.000003075955,0.000005137175,0.0000152404,0.00001351413,0.9913443,0.0003945578,0.007233957,0.0008167697,0.000004488965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06952526,0.002933847,0.921753,0.0004913365,0.0001111,0.00003012207,0.00006073375,0.0001074209,0.004987111],"genre_scores_gemma":[0.9546859,0.001272674,0.04100785,0.00005233646,0.0001255253,0.00003229409,0.00003552651,0.00003974654,0.002748158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002137741,"threshold_uncertainty_score":0.006688178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01157240559643124,"score_gpt":0.1964715250601729,"score_spread":0.1848991194637417,"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."}}