{"id":"W4205681265","doi":"10.1109/tvt.2022.3143174","title":"Resource Allocation for URLLC-Oriented Two-Way UAV Relaying","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Flexibility (engineering); Resource allocation; Optimization problem; Constraint (computer-aided design); Mathematical optimization; Resource management (computing); Software deployment; Wireless; Transmission (telecommunications); Distributed computing; Computer network; Engineering; Algorithm; Telecommunications; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002685819,0.0001933449,0.0002114205,0.0007186257,0.0005695368,0.00001483739,0.0005294821,0.0001892222,0.00005677529],"category_scores_gemma":[0.00001013818,0.0002483705,0.0001194832,0.0009142093,0.00008678214,0.00008673347,0.000009055258,0.0008684096,0.00001401548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003251829,"about_ca_system_score_gemma":0.00001876477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000101683,"about_ca_topic_score_gemma":0.00001746337,"domain_scores_codex":[0.9988006,0.0000698247,0.0003280446,0.0002908038,0.0002075314,0.000303148],"domain_scores_gemma":[0.9988032,0.00009605299,0.00005910602,0.0009282429,0.00007200381,0.00004141506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007190527,0.0003898288,0.00001507461,0.00007458934,0.0002281214,0.000009702931,0.0005985923,0.7462867,0.1321688,0.02445059,0.00201937,0.09368671],"study_design_scores_gemma":[0.001115835,0.0003123367,0.00000683099,0.0000355348,0.00007287216,0.00008207408,0.0008923769,0.2103001,0.4534974,0.001859445,0.3312919,0.0005333462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07854283,0.0002700579,0.9137384,0.001854432,0.000243438,0.0006945347,0.00005143381,0.004207248,0.0003975924],"genre_scores_gemma":[0.9870154,0.00005806756,0.01034197,0.0001242483,0.00001338752,0.002231191,0.00003277168,0.00008105122,0.0001019619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9084725,"threshold_uncertainty_score":0.9999968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083041089387318,"score_gpt":0.2373069033760594,"score_spread":0.2264764924821862,"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."}}