{"id":"W1966517505","doi":"10.1109/glocom.2014.7037374","title":"Statistical modeling of spatial traffic distribution with adjustable heterogeneity and B S-correlation in wireless cellular networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Point process; Spatial correlation; Poisson distribution; Cellular network; Traffic generation model; Wireless network; Poisson point process; Correlation; Base station; Correlation coefficient; Distribution (mathematics); Wireless; Real-time computing; Statistics; Mathematics; Computer network; Telecommunications; Machine learning","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":[0.0001055529,0.00008829318,0.0001465719,0.00002810269,0.00001803586,0.000008241895,0.00002337021,0.00006560087,0.000002703016],"category_scores_gemma":[0.00000896563,0.00008335109,0.000007091229,0.00008103906,0.00001603978,0.0001180874,0.000006917719,0.0000752605,3.940995e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004355276,"about_ca_system_score_gemma":0.000004077623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007938906,"about_ca_topic_score_gemma":0.00039939,"domain_scores_codex":[0.9994504,0.00002556904,0.0002112508,0.0001175873,0.00006490818,0.0001302899],"domain_scores_gemma":[0.9997929,0.00003357743,0.00002654004,0.00008271731,0.00003086707,0.00003344355],"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":[0.00001515461,0.000008061799,0.001894052,0.00004393693,0.000003735503,3.528027e-7,0.00001924836,0.9944662,0.0001789912,0.0006445375,0.000001312371,0.002724427],"study_design_scores_gemma":[0.0003670966,0.00003055561,0.000435612,0.00003685317,0.000008022149,0.000001312368,0.00001677529,0.9985226,0.0004708411,0.00001600495,0.000001369016,0.00009296563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3765124,0.00002688025,0.6232549,7.801657e-7,0.00002980947,0.00008888818,0.000004939096,0.00004261533,0.00003880531],"genre_scores_gemma":[0.9943918,0.00001178598,0.005391283,8.986346e-7,0.00002226036,0.000007441581,0.0001566261,0.00001605564,0.000001871539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6178794,"threshold_uncertainty_score":0.3398959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005087152523909391,"score_gpt":0.1850523358447455,"score_spread":0.1799651833208361,"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."}}