{"id":"W4405490148","doi":"10.1109/iccspa61559.2024.10794379","title":"Trustworthy Aggregation for Aerial Federated Learning in Heterogeneous Client Environments","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Trustworthiness; Computer science; Federated learning; Human–computer interaction; Artificial intelligence; Computer security","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":[0.002621925,0.0005337442,0.0009287507,0.0004997582,0.0009359448,0.001355485,0.001548926,0.0009249978,0.0008943877],"category_scores_gemma":[0.005949461,0.0002351963,0.0003868538,0.0005670832,0.0007200317,0.001994665,0.00242298,0.001128062,0.0002566521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240877,"about_ca_system_score_gemma":0.00161806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004356544,"about_ca_topic_score_gemma":0.004261054,"domain_scores_codex":[0.9988787,0.0003295747,0.00007226987,0.0002483385,0.0002628158,0.0002083067],"domain_scores_gemma":[0.9974342,0.0009618148,0.0002995793,0.0007322696,0.0003899076,0.0001822091],"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":[0.0003870107,0.000169435,0.003723378,0.00005524391,0.00006790472,0.0002262917,0.0002951252,0.8070896,0.004099999,0.01259316,0.002247702,0.1690452],"study_design_scores_gemma":[0.000007142902,0.00002563082,0.0001802459,0.000003644485,0.000003919478,0.00002504296,0.00003704832,0.9933281,0.001084488,0.005004551,0.000297061,0.000003118622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.117153,0.0003027268,0.8779074,0.0004452381,0.00004906986,0.00009830669,0.00006695934,0.001966643,0.002010676],"genre_scores_gemma":[0.935679,0.00005977434,0.06295523,0.00009102382,0.00001942774,0.00004673834,0.00009854653,0.0000408638,0.001009444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004356544,"threshold_uncertainty_score":0.01386619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0233111136785397,"score_gpt":0.2669823322600883,"score_spread":0.2436712185815486,"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."}}