{"id":"W2036994083","doi":"10.1002/wcm.179","title":"A QoS‐based charging and resource allocation framework for next generation wireless networks","year":2003,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Quality of service; Resource allocation; Computer network; Bandwidth (computing); Wireless network; Bandwidth allocation; Wireless; Revenue; The Internet; Resource management (computing); Telecommunications; World Wide Web","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003539462,0.0002344187,0.000253547,0.0001033334,0.0007129356,0.0001646057,0.0002328786,0.0001683544,0.000002249909],"category_scores_gemma":[0.0000336655,0.0002783378,0.00004044814,0.0003104268,0.000109578,0.0001996604,0.00007027399,0.0002921341,5.267107e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006860952,"about_ca_system_score_gemma":0.00001942005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003406822,"about_ca_topic_score_gemma":0.000009370072,"domain_scores_codex":[0.9987779,0.0001234122,0.0003898855,0.0002953095,0.00009091393,0.0003226386],"domain_scores_gemma":[0.9983068,0.000622692,0.000128859,0.0007399916,0.0001044429,0.0000972155],"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":[0.000003536071,0.00002823069,0.0001914588,0.00005720826,0.00001992649,1.398185e-7,0.0004384378,0.8514218,0.001096068,0.02425563,0.00005377853,0.1224338],"study_design_scores_gemma":[0.0003687731,0.00003037925,0.00003726788,0.0001773973,0.00002291862,0.000004589753,0.00030281,0.9922565,0.0004185897,0.0001453128,0.005946597,0.0002889053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1091439,0.005051682,0.8845088,0.0000712554,0.0001476744,0.0006545306,0.000003502513,0.000285568,0.0001330722],"genre_scores_gemma":[0.845901,0.001540615,0.1518538,0.00009128761,0.0001522273,0.0002374573,0.0001503355,0.00006713818,0.000006094433],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7367572,"threshold_uncertainty_score":0.9999669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03007556763250247,"score_gpt":0.2616503546865096,"score_spread":0.2315747870540071,"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."}}