{"id":"W4400276886","doi":"10.1109/wcnc57260.2024.10571118","title":"Delay and Overhead Efficient Transmission Scheduling for Federated Learning in UAV Swarms","year":2024,"lang":"en","type":"article","venue":"","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Overhead (engineering); Scheduling (production processes); Processor scheduling; Distributed computing; Embedded system; Computer network; Operating system; Resource (disambiguation); Engineering","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":[0.001255278,0.0005810241,0.0006883321,0.0002849254,0.0004645699,0.0005550449,0.000991957,0.0004836835,0.0007521115],"category_scores_gemma":[0.002917125,0.0001999111,0.0002547491,0.0003725771,0.000485615,0.0009551939,0.0008951344,0.0005370565,0.0001175409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006983468,"about_ca_system_score_gemma":0.0007616128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001993069,"about_ca_topic_score_gemma":0.001595309,"domain_scores_codex":[0.9994468,0.0001741629,0.00003079151,0.0001227808,0.0001262605,0.00009923131],"domain_scores_gemma":[0.9987959,0.0005154018,0.0002422889,0.0001789041,0.0001839689,0.00008359525],"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":[0.0002129822,0.00008345945,0.0007020574,0.00004946983,0.00002172416,0.00008289625,0.0000923095,0.9409265,0.003895349,0.006282703,0.000662942,0.04698766],"study_design_scores_gemma":[0.00000562747,0.00004411001,0.00007304638,0.000001787498,0.000002683148,0.00001014732,0.00001236465,0.9976664,0.0007668955,0.001282119,0.0001327666,0.000002002593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08082692,0.0002618582,0.9171224,0.0001302286,0.00006106916,0.0000344635,0.00002734674,0.0002705627,0.001265162],"genre_scores_gemma":[0.9739981,0.00005846716,0.02523553,0.00002596791,0.00001734243,0.00002520942,0.00002351731,0.00001394034,0.0006020018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001993069,"threshold_uncertainty_score":0.006638587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006809831280646031,"score_gpt":0.2273532291497568,"score_spread":0.2205433978691108,"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."}}