{"id":"W4408315684","doi":"10.1007/s12083-025-01903-2","title":"Dependency-aware task collaborative offloading and resource allocation in UAV enabled edge computing","year":2025,"lang":"en","type":"article","venue":"Peer-to-Peer Networking and Applications","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Natural Science Foundation of Hunan Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Dependency (UML); Task (project management); Resource allocation; Edge computing; Distributed computing; Enhanced Data Rates for GSM Evolution; Mobile edge computing; Resource (disambiguation); Resource management (computing); Computer architecture; Computer network; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009626878,0.000211228,0.0002560093,0.0003394021,0.0006762724,0.0004376578,0.0004934304,0.00009434848,3.312144e-7],"category_scores_gemma":[0.00006887416,0.0002339813,0.00002492552,0.002378854,0.00003712792,0.0001384798,0.0005896908,0.0002558774,0.00001113155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009071755,"about_ca_system_score_gemma":0.0001013772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005842027,"about_ca_topic_score_gemma":0.00003145008,"domain_scores_codex":[0.9980605,0.00008839503,0.0003798802,0.0007274914,0.000280765,0.0004630034],"domain_scores_gemma":[0.9986232,0.0003683493,0.00009711544,0.0004153926,0.0003317023,0.0001642716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002230408,0.0001344471,0.01568609,0.0001097996,0.0000619817,0.000007791954,0.01209639,0.01349927,0.001002383,0.0299192,0.04571519,0.8817452],"study_design_scores_gemma":[0.0005391676,0.00004346108,0.008673384,0.0004050396,0.00002289856,0.00001083616,0.0004259744,0.3161301,0.0002707726,0.004038401,0.6689245,0.0005154526],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02737388,0.000495036,0.9530289,0.01173686,0.0008625604,0.0009317517,0.000001440704,0.0002445579,0.005324985],"genre_scores_gemma":[0.9754049,0.00001424632,0.02046787,0.001159701,0.001368148,0.0001539031,0.0000216218,0.00001780891,0.001391824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.948031,"threshold_uncertainty_score":0.9541482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009747758509713336,"score_gpt":0.2657448681666465,"score_spread":0.2559971096569332,"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."}}