{"id":"W2584333276","doi":"10.1109/glocom.2016.7841794","title":"Energy Efficient Joint User Association and Power Allocation in a Two-Tier Heterogeneous Network","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Efficient energy use; Mathematical optimization; Quality of service; Relaxation (psychology); Association scheme; Power (physics); Iterative method; Convex optimization; Heterogeneous network; Energy (signal processing); Constraint (computer-aided design); Joint (building); Regular polygon; Algorithm; Computer network; Mathematics; Engineering; Wireless network","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":[0.0001317369,0.00009390459,0.0001096463,0.00005732692,0.00001805493,0.00001433322,0.00002670407,0.00005381656,0.0000351161],"category_scores_gemma":[0.00002171462,0.00007371829,0.00001634053,0.0001122702,0.00000499108,0.00008381931,0.0000153474,0.00002679366,0.0000123407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285195,"about_ca_system_score_gemma":0.000004703322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002469957,"about_ca_topic_score_gemma":0.0001883701,"domain_scores_codex":[0.9993567,0.00002626266,0.0002047049,0.0001326623,0.00008390166,0.0001957447],"domain_scores_gemma":[0.9997384,0.00004043722,0.0000409163,0.0001072663,0.00003732182,0.00003568434],"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":[0.000002449383,0.00000671943,0.001440214,0.000003573001,0.00001063599,8.421975e-7,0.00006144643,0.9923152,0.003441576,0.0006746451,0.0002760527,0.001766684],"study_design_scores_gemma":[0.001672941,0.00003676112,0.002660058,0.0001517403,0.0000118004,0.000009637702,0.00002551895,0.9769473,0.01221707,0.0003572878,0.005431393,0.0004784843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1013462,0.0002658856,0.8961072,0.00007447461,0.0003206105,0.0001247715,0.000001310981,0.0001765167,0.001583083],"genre_scores_gemma":[0.9967511,0.00004558241,0.002252683,0.00004004436,0.00005588275,0.00002653905,0.000002693761,0.00002462335,0.0008008681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8954049,"threshold_uncertainty_score":0.3006145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004754343000389087,"score_gpt":0.1948957258462528,"score_spread":0.1901413828458637,"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."}}