{"id":"W2148562694","doi":"10.1109/glocom.2013.6831376","title":"Optimizing user association and frequency reuse for heterogeneous network under stochastic model","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Reuse; Base station; Telecommunications link; Cellular network; Heterogeneous network; Maximization; Enhanced Data Rates for GSM Evolution; Mathematical optimization; Wireless network; Computer network; Distributed computing; Wireless; Telecommunications; Engineering; Mathematics","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":[0.00007127672,0.0001216602,0.0001339866,0.00003139197,0.00006211714,0.00005237122,0.00006951275,0.0001028873,0.00001756295],"category_scores_gemma":[0.00005264071,0.000124564,0.00002603594,0.00006172297,0.000004870194,0.0003116296,0.00002237402,0.00005511973,0.00001184533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795412,"about_ca_system_score_gemma":0.000006255775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001361978,"about_ca_topic_score_gemma":0.00002204171,"domain_scores_codex":[0.9993376,0.000007996373,0.0001926577,0.0001407405,0.00006293918,0.0002581196],"domain_scores_gemma":[0.9995462,0.00008674439,0.00004469557,0.0001845227,0.00008216054,0.00005569447],"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":[7.84006e-7,0.000002395631,0.00003481701,0.00001650049,0.0000215829,4.250387e-8,0.00007064587,0.9976168,0.000546076,0.000518978,0.001081214,0.00009013258],"study_design_scores_gemma":[0.0002232746,0.00001073467,0.00001597802,0.00001575747,0.00001414043,0.000001528837,0.00001715422,0.993296,0.00008285201,0.006169201,0.000006227157,0.0001470973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009987497,0.0002502911,0.9883444,0.00005174624,0.0001583948,0.0005496065,0.000003588976,0.0003085745,0.0003459314],"genre_scores_gemma":[0.6394027,0.00001568029,0.3595805,0.00006018087,0.00008987114,0.0001703399,0.00001086044,0.00005078827,0.0006191505],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6294152,"threshold_uncertainty_score":0.5079572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160901908654812,"score_gpt":0.2126287062146718,"score_spread":0.2010196871281237,"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."}}