{"id":"W2792238983","doi":"10.1109/access.2018.2803788","title":"Multiple Drone-Cell Deployment Analyses and Optimization in Drone Assisted Radio Access Networks","year":2018,"lang":"en","type":"article","venue":"IEEE Access","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Drone; Computer science; Base station; Software deployment; Particle swarm optimization; Backhaul (telecommunications); Computer network; Real-time computing; Distributed computing; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003315908,0.0006001784,0.0004437854,0.0004702983,0.000298641,0.0007350581,0.0005272251,0.0006377663,0.0008275917],"category_scores_gemma":[0.001039959,0.0003730406,0.0004304649,0.0004149865,0.0004440787,0.000936853,0.000545633,0.0004468841,0.0001031153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000631765,"about_ca_system_score_gemma":0.0004025211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005760692,"about_ca_topic_score_gemma":0.00457971,"domain_scores_codex":[0.9998139,0.00006168403,0.000006739998,0.00003921066,0.0000459789,0.00003252994],"domain_scores_gemma":[0.9996359,0.0001976093,0.00006164546,0.0000228381,0.00006000042,0.00002190094],"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":[0.000009436905,0.000007838443,0.0005374908,0.0000150116,0.00001183075,0.00004677043,0.00001621778,0.9920433,0.0008995471,0.0023865,0.0001004872,0.003925547],"study_design_scores_gemma":[8.178269e-7,0.000007496243,0.0001627664,0.000001310097,0.000003042339,0.000009587567,0.00000940636,0.9991143,0.0001413779,0.0004396918,0.0001086288,0.000001607189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1824442,0.001004764,0.8098149,0.0002789134,0.00004230654,0.00004000128,0.0000598171,0.0001004613,0.006214598],"genre_scores_gemma":[0.9605006,0.0005309916,0.03711675,0.00004459659,0.00001805408,0.00003288861,0.00005230344,0.00002493182,0.001678782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005760692,"threshold_uncertainty_score":0.01145434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04026161968819993,"score_gpt":0.3107910306840001,"score_spread":0.2705294109958002,"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."}}