{"id":"W3080211198","doi":"10.1109/access.2020.3018861","title":"Backhaul-Aware Optimization of UAV Base Station Location and Bandwidth Allocation for Profit Maximization","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Backhaul (telecommunications); Base station; Profit maximization; Bandwidth allocation; Computer science; Maximization; Bandwidth (computing); Profit (economics); Computer network; Dynamic bandwidth allocation; Mathematical optimization; Microeconomics; Economics; 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":[0.00009410342,0.0001338944,0.0001451247,0.00009619057,0.00006828604,0.00008115615,0.0001281351,0.00008870364,0.00002745917],"category_scores_gemma":[0.00004446651,0.0001496583,0.00002256703,0.0005222742,0.00002487211,0.0007412738,0.00001360997,0.00004805305,0.00000244044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003965246,"about_ca_system_score_gemma":0.00003010711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001484833,"about_ca_topic_score_gemma":0.000009254507,"domain_scores_codex":[0.9991789,0.00001727879,0.0003324219,0.0002206281,0.00013038,0.0001203755],"domain_scores_gemma":[0.9992306,0.00004455872,0.0001226179,0.0001432501,0.0003889376,0.00007002251],"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":[0.00002446713,0.000008816781,0.0008169964,0.0003798839,0.00001482576,4.957091e-8,0.0002332164,0.9917349,0.001408528,0.0004008066,0.0006835356,0.004293945],"study_design_scores_gemma":[0.0005151539,0.00003515073,0.00115048,0.00002638714,0.00003856718,4.563253e-7,0.00004405487,0.9800211,0.01780882,0.0001216652,0.00008662401,0.0001515042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01683433,0.00007574544,0.9813227,0.0004119845,0.00009774869,0.0009253829,0.00005198341,0.0001732156,0.0001069266],"genre_scores_gemma":[0.9717617,0.0002281848,0.02672774,0.0001142429,0.00009674952,0.0002421626,0.0007723813,0.00004446992,0.0000123809],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9549274,"threshold_uncertainty_score":0.6102887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02745150603055576,"score_gpt":0.2566893568225934,"score_spread":0.2292378507920376,"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."}}