{"id":"W2413171354","doi":"10.1109/iccnc.2017.7876094","title":"Decentralized AP selection in large-scale wireless LANs considering multi-AP interference","year":2017,"lang":"en","type":"preprint","venue":"2017 International Conference on Computing, Networking and Communications (ICNC)","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Telecommunications link; Interference (communication); Computer science; Signal-to-interference-plus-noise ratio; Throughput; Computer network; Signal-to-noise ratio (imaging); Selection algorithm; Channel (broadcasting); Selection (genetic algorithm); Wireless; Telecommunications; Power (physics); Physics","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":[0.001612214,0.000783494,0.001495252,0.0005986106,0.001362906,0.001339384,0.001963798,0.001033338,0.0006236982],"category_scores_gemma":[0.003657559,0.0005909425,0.0004559907,0.0009641653,0.001062774,0.001458594,0.001635846,0.0008529864,0.000215303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040338,"about_ca_system_score_gemma":0.001016023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00288377,"about_ca_topic_score_gemma":0.003264424,"domain_scores_codex":[0.9985447,0.0005624333,0.00004902478,0.0002829194,0.0003441969,0.0002166775],"domain_scores_gemma":[0.997147,0.001505222,0.0004264213,0.0003319733,0.0004024458,0.0001869272],"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":[0.0001688036,0.00007977286,0.002166519,0.00007463434,0.00006342282,0.0004467961,0.0001269963,0.9507085,0.007600062,0.006469831,0.0007123716,0.03138222],"study_design_scores_gemma":[0.00001780856,0.00005087251,0.0003675537,0.000002058504,0.00001819147,0.0000776477,0.00003518809,0.996657,0.0006548392,0.001901076,0.0002103557,0.000007291749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1247454,0.0008298671,0.8709762,0.0002789681,0.00007308002,0.00007776317,0.00003789881,0.0005257854,0.002455151],"genre_scores_gemma":[0.9680873,0.000205532,0.03083114,0.00003318447,0.00007384504,0.00004681439,0.00003047924,0.00001591882,0.0006757706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00288377,"threshold_uncertainty_score":0.008526325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129335136256484,"score_gpt":0.368921600868739,"score_spread":0.239586464612255,"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."}}