{"id":"W2291391292","doi":"10.1109/glocomw.2015.7414115","title":"AP Association Optimization and CCA Threshold Adjustment in Dense WLANs","year":2015,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Throughput; Computer network; Telecommunications link; Interference (communication); Software deployment; Wireless; Channel (broadcasting); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003587198,0.00005393471,0.00007226678,0.0000371085,0.00001982319,0.00009017869,0.0001218778,0.00005312304,0.000006809969],"category_scores_gemma":[0.00001485437,0.0000461305,0.000009165976,0.0001584463,0.000003991041,0.0002718572,0.00007701144,0.00005097224,0.000007169781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009476556,"about_ca_system_score_gemma":0.00003147705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003801658,"about_ca_topic_score_gemma":0.00007184079,"domain_scores_codex":[0.9994193,0.00003570277,0.0001098568,0.0001485737,0.000157178,0.0001293933],"domain_scores_gemma":[0.9996913,0.00003020807,0.00004564178,0.0001269987,0.00004491997,0.00006090933],"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":[0.00002649173,0.000216177,0.1192097,0.00001956363,0.00002187845,0.00001542481,0.002779961,0.7257519,0.00002829091,0.08605351,0.03376065,0.03211649],"study_design_scores_gemma":[0.0005619493,0.00005459355,0.004978626,0.00001177074,0.000001251807,0.000001405071,0.00001716847,0.9915797,0.00005554531,0.001585943,0.001069721,0.00008240094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009145883,0.0001494681,0.9774428,0.002091748,0.0002329556,0.002461085,5.458302e-7,0.0001181768,0.008357335],"genre_scores_gemma":[0.8604406,0.00008401447,0.1337951,0.001615294,0.0002616577,0.001428127,0.00000761236,0.0000141979,0.002353451],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8512947,"threshold_uncertainty_score":0.1881147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02532543824538612,"score_gpt":0.2554714881059237,"score_spread":0.2301460498605376,"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."}}