{"id":"W2158231564","doi":"10.1145/2641798.2641819","title":"Handoff rate analysis in heterogeneous cellular networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Bell Canada Enterprises","keywords":"Computer science; Handover; Correctness; Randomness; Network topology; Overhead (engineering); Computer network; Mobility model; Cellular network; Distributed computing; Heterogeneous network; Trajectory; Wireless network; Algorithm; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001200208,0.0001054077,0.0002212988,0.0003436067,0.00008506344,0.0002203264,0.001670346,0.00006718576,0.00006246209],"category_scores_gemma":[0.00003384696,0.00009430859,0.0001027717,0.002336988,0.00003958637,0.0001823541,0.0006555342,0.0002136002,0.00006314788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003642536,"about_ca_system_score_gemma":0.00001821226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001327419,"about_ca_topic_score_gemma":0.0005842316,"domain_scores_codex":[0.9981849,0.0006329292,0.0002586788,0.0003373183,0.0002130178,0.0003731592],"domain_scores_gemma":[0.9977981,0.0003615914,0.00005218944,0.001610613,0.0000675883,0.0001099438],"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":[0.000004297005,0.00005133542,0.005562005,0.000001951766,0.00007285805,0.000008161963,0.00006601276,0.9528639,0.0001682467,0.01556632,0.0002395046,0.02539545],"study_design_scores_gemma":[0.0001918118,0.00001687915,0.003052892,0.000003047623,0.000006632867,7.551682e-7,0.000001477873,0.9942803,0.0005943689,0.0004065013,0.00133388,0.0001114165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02673967,0.0002099905,0.9688001,0.0006919382,0.00005076366,0.00009169136,7.935098e-8,0.000109243,0.003306569],"genre_scores_gemma":[0.9905713,0.00007079382,0.008476052,0.0002856082,0.00003546067,0.00001961543,0.000005065985,0.000006808724,0.0005293104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9638316,"threshold_uncertainty_score":0.3845793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433050859064766,"score_gpt":0.2516535831025933,"score_spread":0.2373230745119456,"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."}}