{"id":"W4417002525","doi":"10.1109/jiot.2025.3640520","title":"Anti-Jamming Task Scheduling in MEC-O-RAN With Hierarchical DRL and Transformer-Based Control","year":2025,"lang":"","type":"article","venue":"IEEE Internet of Things Journal","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Science and Engineering Research Council; Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Reinforcement learning; Scheduling (production processes); Markov decision process; Jamming; Estimator; Optimization problem; Quality of service; Job shop scheduling; Markov process","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002030161,0.0005208235,0.001090007,0.0008905087,0.0002252825,0.0008157946,0.001319851,0.0002599508,0.00002928475],"category_scores_gemma":[0.0001721223,0.0004376716,0.0002854148,0.0008273558,0.0004411079,0.00110567,0.00005808498,0.00236877,0.00000229232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001395414,"about_ca_system_score_gemma":0.0006353917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002056903,"about_ca_topic_score_gemma":0.00003711281,"domain_scores_codex":[0.9958794,0.0003183362,0.001464883,0.0007069972,0.0007298799,0.0009005097],"domain_scores_gemma":[0.9975016,0.0009049009,0.0006145248,0.0003605908,0.0002853834,0.0003330728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007144726,0.002159489,0.1730302,0.001586183,0.002307024,0.002855621,0.03484324,0.1165205,0.01822715,0.00826172,0.0009564015,0.6321077],"study_design_scores_gemma":[0.01056648,0.001577921,0.003653619,0.009210375,0.0002079236,0.0006994789,0.0001955447,0.9630288,0.007219002,0.002507902,0.0004762493,0.0006566917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.424099,0.001414061,0.5705633,0.002489089,0.001054112,0.0001958015,0.000002151024,0.00002767304,0.0001549062],"genre_scores_gemma":[0.9752117,0.0002235121,0.02254845,0.00172087,0.00017679,0.000005874454,5.58184e-7,0.00003086014,0.00008135112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8465083,"threshold_uncertainty_score":0.9999328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007850121364263229,"score_gpt":0.2341376444583489,"score_spread":0.2262875230940857,"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."}}