{"id":"W1616845905","doi":"10.48550/arxiv.1008.5170","title":"General Model for Single and Multiple Channels WLANs with Quality of Service Support","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"HiperLAN; Computer network; Computer science; Throughput; Quality of service; Channel (broadcasting); Telecommunications link; Data as a service; Wireless; Wireless network; Data transmission; Transmission (telecommunications); Service (business); Wireless lan; Telecommunications","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":[0.001958226,0.001743677,0.002401879,0.001667755,0.001139994,0.003753457,0.005872283,0.004864399,0.009116777],"category_scores_gemma":[0.004821913,0.001132337,0.001997067,0.002491711,0.001702231,0.005596619,0.001914888,0.003321021,0.003334458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003484332,"about_ca_system_score_gemma":0.002495492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01336285,"about_ca_topic_score_gemma":0.00612622,"domain_scores_codex":[0.9969274,0.0006609581,0.0001485151,0.0007148133,0.0008423607,0.0007059319],"domain_scores_gemma":[0.9977193,0.0007824002,0.0003326355,0.0002562346,0.0007540267,0.0001552432],"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":[0.0001321816,0.0001319527,0.001120106,0.0001724503,0.00008382285,0.00059017,0.0002484124,0.7651194,0.004110425,0.2173356,0.00422803,0.006727472],"study_design_scores_gemma":[0.00004745514,0.00004344417,0.0002783758,0.00001984844,0.0000329184,0.0001700794,0.00005257627,0.9592569,0.0003219649,0.0369962,0.002741631,0.00003855656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04347686,0.001491372,0.9259952,0.002477702,0.0004145362,0.0003652155,0.002072774,0.001046553,0.02265986],"genre_scores_gemma":[0.8207936,0.003866752,0.08926743,0.001205568,0.0009316898,0.001641169,0.002050233,0.000554105,0.07968953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01336285,"threshold_uncertainty_score":0.03049862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1476626929317247,"score_gpt":0.2287583512974756,"score_spread":0.08109565836575086,"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."}}