{"id":"W4415124089","doi":"10.1109/tccn.2025.3620361","title":"Learning-Based Collaboration for Secure Transmission Effectiveness Maximization in Low Altitude MEC Systems","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Eavesdropping; Mobile edge computing; Transmission (telecommunications); Maximization; Secure transmission; Mobile device; Resource allocation; Scheme (mathematics); Wireless; Transmission delay","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":[0.0009585466,0.000818256,0.0008763941,0.0002714648,0.0005322521,0.0007358221,0.001056307,0.0007855027,0.001609491],"category_scores_gemma":[0.002707389,0.0002930371,0.0003811198,0.0003551572,0.0007704757,0.00127925,0.001560874,0.001095476,0.0002101961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008558835,"about_ca_system_score_gemma":0.001152264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003919458,"about_ca_topic_score_gemma":0.003500111,"domain_scores_codex":[0.9993723,0.0001677084,0.00002958209,0.000152708,0.0001288964,0.000148811],"domain_scores_gemma":[0.9989355,0.0005361353,0.0001620552,0.00008037349,0.0001926586,0.00009318421],"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":[0.00009781396,0.0000424608,0.000580136,0.00004194443,0.0000211375,0.00009775539,0.000062246,0.9686618,0.002249436,0.005320318,0.0005774715,0.02224754],"study_design_scores_gemma":[0.000005411605,0.00002064527,0.00004026888,0.000002027319,0.000003121956,0.00001033734,0.000005362348,0.9980343,0.000305093,0.001481691,0.00008945774,0.000002256779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06009776,0.0003311643,0.9349425,0.000298047,0.00003880951,0.00004716674,0.00004435475,0.0002403496,0.003959888],"genre_scores_gemma":[0.9781979,0.00009275417,0.02030112,0.00007339034,0.00001377463,0.00004513632,0.0000288867,0.00001582248,0.001231113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003919458,"threshold_uncertainty_score":0.007793248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041405765531887,"score_gpt":0.258587548182105,"score_spread":0.2481734905267861,"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."}}