{"id":"W1636291033","doi":"10.1109/wirles.2005.1549437","title":"Adaptive Contention-Window MAC Algorithms for QoS-Enabled Wireless LANs","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Throughput; Computer network; Wireless lan; Quality of service; Window (computing); Wireless; Algorithm; Real-time computing; 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":[0.002752144,0.0007922858,0.0005961876,0.00101469,0.0007664411,0.0008990377,0.002181456,0.000573988,0.001400073],"category_scores_gemma":[0.007218165,0.0003515038,0.000253401,0.00104442,0.000758789,0.002076406,0.0008553605,0.001367352,0.0003338521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008579902,"about_ca_system_score_gemma":0.00104502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001912277,"about_ca_topic_score_gemma":0.001863105,"domain_scores_codex":[0.9990062,0.0002906143,0.00007978226,0.0001137995,0.0004212692,0.00008835211],"domain_scores_gemma":[0.9974015,0.001385904,0.0002311732,0.0004126287,0.0004837778,0.00008505602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004679032,0.0002114858,0.001139203,0.0002025108,0.00008773408,0.0001079582,0.0003234284,0.4088404,0.02261722,0.1372334,0.005053741,0.423715],"study_design_scores_gemma":[0.00004388768,0.00006314633,0.0001394297,0.00001324838,0.00001656734,0.00004715836,0.00001644925,0.9753816,0.003788612,0.01667268,0.00379922,0.00001816002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008058378,0.00116329,0.9886308,0.000125637,0.0001107237,0.00006718485,0.00001616853,0.0008095715,0.001018282],"genre_scores_gemma":[0.32134,0.001800457,0.6737638,0.0001405589,0.0002497722,0.0003500796,0.00008468558,0.0001490386,0.00212162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002752144,"threshold_uncertainty_score":0.01455486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03832242105163671,"score_gpt":0.2817302825721416,"score_spread":0.2434078615205049,"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."}}