{"id":"W2175185983","doi":"10.48550/arxiv.1312.1957","title":"Uplink Interference Analysis for Two-tier Cellular Networks with Diverse Users under Random Spatial Patterns","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Base station; Stochastic geometry; Telecommunications link; Interference (communication); Cellular network; Heterogeneous network; Tier 2 network; Computer network; Telecommunications; Wireless network; Mathematics; Wireless; Channel (broadcasting); Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001030704,0.0004829225,0.0006571112,0.0004003786,0.0001011549,0.00008078942,0.0004902466,0.0003302112,0.0001253221],"category_scores_gemma":[0.00000753846,0.0005168763,0.0003196757,0.0004474936,0.00006661731,0.0002656712,0.0002797012,0.0004640023,0.00001737212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003438872,"about_ca_system_score_gemma":0.00003187614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008008468,"about_ca_topic_score_gemma":0.001002636,"domain_scores_codex":[0.9984111,0.00005959911,0.0002797309,0.0007724902,0.00005765598,0.0004194833],"domain_scores_gemma":[0.9985656,0.0001006114,0.0001901382,0.0007645612,0.0002151861,0.000163938],"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":[0.0001349113,0.00001774401,0.009279314,0.0001115079,0.001421168,0.00002248704,0.0001070288,0.9884647,0.00001808244,0.0003094283,0.00002621863,0.00008745956],"study_design_scores_gemma":[0.002095376,0.00003364904,0.0002594309,0.0001215542,0.001447822,5.56589e-7,0.0001881464,0.9949475,0.00009292331,0.0002109334,0.000009998238,0.0005921457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1455386,0.00004511664,0.8526434,0.000003506374,0.0004849966,0.0008352022,0.00004863249,0.0002778873,0.000122619],"genre_scores_gemma":[0.9969219,0.00009663957,0.001839442,0.00001298282,0.0001471052,0.00001460572,0.0003674673,0.00008296285,0.0005169174],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8513833,"threshold_uncertainty_score":0.9997283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382491876846548,"score_gpt":0.1729492720104412,"score_spread":0.1391243532419758,"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."}}