{"id":"W3133982043","doi":"10.1109/tvt.2021.3065084","title":"UAV Communications for Sustainable Federated Learning","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Research Foundation of Korea; Pusan National University","keywords":"Wireless; Leverage (statistics); Wireless power transfer; Wireless network; Transmitter power output; Scheduling (production processes); Transmission (telecommunications); Boosting (machine learning)","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":[0.0003887374,0.0004543595,0.0003438406,0.0002650326,0.0004360988,0.0006867707,0.0005691886,0.0004971007,0.001817047],"category_scores_gemma":[0.0007845254,0.0001040902,0.00026145,0.000447202,0.0003313188,0.001071957,0.00104335,0.0005824152,0.0003573782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004457191,"about_ca_system_score_gemma":0.0005923756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001139663,"about_ca_topic_score_gemma":0.001954146,"domain_scores_codex":[0.9997802,0.00005829697,0.00000828942,0.00003917219,0.00006002305,0.00005387348],"domain_scores_gemma":[0.9997506,0.0001012898,0.00002847712,0.00004818601,0.00004754217,0.00002390856],"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":[0.0001342736,0.00008885718,0.001151542,0.0001688719,0.00004261898,0.0002404775,0.00009102069,0.6651461,0.01073676,0.05679275,0.00786406,0.2575427],"study_design_scores_gemma":[0.000007112162,0.00005660361,0.0001942409,0.00001598315,0.000007797324,0.00008730444,0.00005583196,0.9701861,0.003587736,0.01848525,0.007310166,0.000005883248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04519652,0.001317838,0.9405376,0.0007148923,0.0001473259,0.00003586137,0.00008900271,0.0006487375,0.01131214],"genre_scores_gemma":[0.9285699,0.0006465208,0.06681059,0.00017605,0.00003375939,0.00003959189,0.0001210358,0.0000392381,0.003563309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001817047,"threshold_uncertainty_score":0.006078601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008019406256754853,"score_gpt":0.2229306386666972,"score_spread":0.2149112324099423,"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."}}