{"id":"W2098047202","doi":"10.1109/pacrim.2007.4313296","title":"Multi-Flow Merging Gain in Scheduling for Flow-Based Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computer network; Quality of service; Wireless; Scheduling (production processes); Radio resource management; Network packet; Wireless network; Distributed 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":[0.00399363,0.0007954278,0.0006936927,0.0007885521,0.0006558885,0.0007870155,0.0009666561,0.0005630262,0.001169375],"category_scores_gemma":[0.008992276,0.0002911501,0.0003386521,0.0009391315,0.001030692,0.002551361,0.001152361,0.0006229197,0.0001381832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266088,"about_ca_system_score_gemma":0.0007457227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008010379,"about_ca_topic_score_gemma":0.001049876,"domain_scores_codex":[0.9987776,0.0004214285,0.00003280183,0.0000979519,0.0004453115,0.0002249998],"domain_scores_gemma":[0.9950531,0.003425556,0.0006010903,0.0003373773,0.0004008691,0.0001820953],"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":[0.001349747,0.0004192051,0.005439212,0.0002004991,0.0001224724,0.0001371531,0.0002815286,0.7199206,0.0418466,0.06217949,0.001096596,0.1670069],"study_design_scores_gemma":[0.00003386559,0.0009281841,0.002364859,0.0000144162,0.00007288994,0.0001394372,0.00003958636,0.9672129,0.01406484,0.01360569,0.001500867,0.00002264538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2941014,0.002184396,0.6962665,0.0003607127,0.0001001044,0.0001702936,0.0000644957,0.0005178845,0.006234188],"genre_scores_gemma":[0.9108636,0.0003485881,0.08790984,0.00007117523,0.00009590342,0.0000574664,0.00003934679,0.00002973324,0.0005843009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00399363,"threshold_uncertainty_score":0.02112061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113491783097536,"score_gpt":0.2425911690609005,"score_spread":0.2314562512299251,"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."}}