{"id":"W3133222151","doi":"10.1109/globecom42002.2020.9347949","title":"Energy and Spectrum Efficient User Association for Backhaul Load Balancing in Small Cell Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Backhaul (telecommunications); Computer science; Base station; Efficient energy use; Software deployment; Computer network; Small cell; Spectral efficiency; Macro; Energy consumption; Maximization; Distributed computing; Engineering; Electrical engineering; Mathematical optimization; Operating system","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":[0.0005954822,0.0005467198,0.0007528907,0.0002777755,0.0004841551,0.0006295198,0.0006994978,0.0005128271,0.001028097],"category_scores_gemma":[0.001584623,0.0001866416,0.0001971506,0.0005819544,0.0004780753,0.0006152815,0.0006160203,0.0003947276,0.0001966032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004766953,"about_ca_system_score_gemma":0.0008905881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001744243,"about_ca_topic_score_gemma":0.003239124,"domain_scores_codex":[0.9996131,0.0001539698,0.00001066671,0.00005290133,0.0001013553,0.00006790729],"domain_scores_gemma":[0.9993013,0.0004390355,0.00008765022,0.0000525487,0.00007969988,0.00003970406],"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":[0.0001056565,0.0001037053,0.0006025617,0.00003478899,0.00001696686,0.0000341135,0.00004304433,0.9418054,0.004591953,0.00463651,0.0006648186,0.04736043],"study_design_scores_gemma":[0.00000639828,0.00002960361,0.0001236165,0.000001417307,0.000002923577,0.00001554885,0.00001029593,0.9977842,0.0008086403,0.001086797,0.000128151,0.000002362636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09700032,0.0004451631,0.899115,0.0001429202,0.0000300157,0.00005125743,0.0000249441,0.0001713658,0.003018937],"genre_scores_gemma":[0.9311872,0.0001942656,0.06723565,0.00003972295,0.00002784733,0.00004834165,0.00002796928,0.0000166758,0.001222335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001744243,"threshold_uncertainty_score":0.003468215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004872943423167686,"score_gpt":0.168611835208849,"score_spread":0.1637388917856813,"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."}}