{"id":"W1589240109","doi":"10.1002/9780470403686.ch21","title":"Subchannel Allocation and Connection Admission Control in OFDMA‐Based IEEE 802.16/WiMAX‐Compliant Infrastructure Wireless Mesh Networks","year":2008,"lang":"en","type":"other","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"WiMAX; Computer network; Computer science; Wireless mesh network; Queueing theory; Admission control; IEEE 802.11s; Resource allocation; IEEE 802; Mesh networking; Service set; Radio resource management; Wireless network; Wireless; Wi-Fi; Telecommunications; Quality of service","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":[0.00007597617,0.000573674,0.0006295741,0.0004424274,0.00006642268,0.00003401055,0.0001454229,0.0008529967,0.0004727744],"category_scores_gemma":[0.00001041877,0.0005820458,0.00006282157,0.0004123328,0.00006001044,0.0001335367,0.00001643802,0.0005232809,0.000006077986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002747175,"about_ca_system_score_gemma":0.00004167464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001026315,"about_ca_topic_score_gemma":0.0004909889,"domain_scores_codex":[0.998323,0.00006674801,0.0004469649,0.0005050802,0.0002208978,0.0004372709],"domain_scores_gemma":[0.9991996,0.00007514119,0.0001936557,0.0003159844,0.00005591677,0.0001597514],"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":[0.00004094999,0.00001842256,0.0002789657,0.0001335246,0.00004601065,0.00000679506,0.00002176826,0.910337,0.0001706145,0.00009602171,0.08129747,0.007552485],"study_design_scores_gemma":[0.001735426,0.00002870664,0.0002520461,0.0005928715,0.00003475155,0.0000100496,0.00001849958,0.9888501,0.0001359672,0.00002933657,0.007710184,0.0006020364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004537869,0.001487846,0.9834933,0.00005871522,0.001126424,0.0009874178,0.00002759387,0.001066125,0.01129879],"genre_scores_gemma":[0.9592184,0.01402442,0.004704597,0.0003799153,0.001358846,0.0003221307,0.000742661,0.001559702,0.01768932],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9787887,"threshold_uncertainty_score":0.9996631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005786085698808544,"score_gpt":0.2009963793453844,"score_spread":0.1952102936465759,"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."}}