{"id":"W2770997863","doi":"10.1109/mcom.2018.1700666","title":"Multi-Tier Drone Architecture for 5G/B5G Cellular Networks: Challenges, Trends, and Prospects","year":2018,"lang":"en","type":"preprint","venue":"IEEE Communications Magazine","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Drone; Cellular network; Computer science; Telecommunications link; Base station; Computer network; Context (archaeology); Spectral efficiency; Wireless network; Software deployment; Distributed computing; Wireless; Telecommunications; Channel (broadcasting); Geography","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":[0.0002229466,0.0004078628,0.0003997875,0.000269733,0.0002578736,0.0001058109,0.001001544,0.0004106508,0.00002257449],"category_scores_gemma":[0.00001885249,0.0004401495,0.0001092171,0.000248714,0.0002113611,0.00006850506,0.0003206458,0.0006449961,0.00002422232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009952939,"about_ca_system_score_gemma":0.00002605422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009410172,"about_ca_topic_score_gemma":0.0003272627,"domain_scores_codex":[0.9986145,0.00005592916,0.0004458562,0.000450246,0.0001104612,0.0003229892],"domain_scores_gemma":[0.9963087,0.0001112591,0.0001487347,0.003115023,0.0001975891,0.0001186363],"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":[0.00003121325,0.0005627227,0.00006075586,0.00116405,0.0004995143,0.000001025072,0.001484678,0.8301516,0.002050071,0.001932957,0.03276432,0.1292971],"study_design_scores_gemma":[0.000584682,0.00003898088,0.0006724538,0.0001552559,0.0001230731,0.000004321426,0.00001124002,0.8472504,0.0001920669,0.0009914358,0.1494537,0.0005224483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009683345,0.08282125,0.9002902,0.003329901,0.001020242,0.002459688,0.0002979742,0.001140174,0.007672256],"genre_scores_gemma":[0.4328368,0.06594042,0.4900536,0.00008051858,0.001151786,0.004132648,0.003424908,0.0003551861,0.002024153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4318685,"threshold_uncertainty_score":0.999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03326704056067363,"score_gpt":0.2596571551252276,"score_spread":0.226390114564554,"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."}}