{"id":"W4412170766","doi":"10.1109/jiot.2025.3587700","title":"An Efficient Online Task Offloading Algorithm for Bilevel UAV-Enabled Mobile Edge Computing","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; National Natural Science Foundation of China","keywords":"Computer science; Mobile edge computing; Task (project management); Edge computing; Mobile computing; Enhanced Data Rates for GSM Evolution; Algorithm; Algorithm design; Computer network; Server; Distributed computing; Artificial intelligence","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":[0.0002600441,0.0007266288,0.0008041407,0.0003197143,0.0005005634,0.0006812639,0.0007642166,0.0005385354,0.001831027],"category_scores_gemma":[0.0009198683,0.0002676793,0.0003451395,0.0004067293,0.0003272662,0.000630536,0.0008120168,0.0006726557,0.0003512085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005308725,"about_ca_system_score_gemma":0.001081336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004594609,"about_ca_topic_score_gemma":0.005607183,"domain_scores_codex":[0.9997833,0.00002959827,0.00001269509,0.00005215078,0.00004012138,0.00008197143],"domain_scores_gemma":[0.9997194,0.0001212724,0.00003574934,0.00002968865,0.00005625062,0.00003755295],"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":[0.000197624,0.0001021046,0.0008820875,0.00009440751,0.00002203437,0.0001115156,0.00009922169,0.8890971,0.008489658,0.004988236,0.002186188,0.09372994],"study_design_scores_gemma":[0.000007173232,0.00001849139,0.00005495553,0.000002125021,0.000001524802,0.00001082379,0.00001216702,0.9984415,0.0003831814,0.0008813205,0.0001848451,0.000001870225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06353176,0.0003340152,0.9315897,0.000161278,0.00006550888,0.00008559947,0.00006250657,0.0005543728,0.003615279],"genre_scores_gemma":[0.801743,0.0001751251,0.1951838,0.00007943581,0.00002814001,0.0001270222,0.0001886506,0.00008012856,0.002394774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004594609,"threshold_uncertainty_score":0.009135783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460961226341278,"score_gpt":0.2914399270506299,"score_spread":0.2768303147872171,"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."}}