{"id":"W3157716736","doi":"10.25073/2588-1086/vnucsce.240","title":"Performance of Orthogonal Frequency Division Multiplexing Based Advanced Encryption Standard","year":2020,"lang":"en","type":"article","venue":"VNU Journal of Science Computer Science and Communication Engineering","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Encryption; Advanced Encryption Standard; Computer network; Physical layer; Wireless; Telecommunications; Channel (broadcasting)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00303349,0.0001249589,0.0002040861,0.0005825461,0.0004688577,0.0002251217,0.002898311,0.00002369478,0.000001854802],"category_scores_gemma":[0.0002195906,0.0001108183,0.00005751702,0.002618257,0.0009262541,0.003470569,0.0005558726,0.0002298527,5.267097e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005634777,"about_ca_system_score_gemma":0.0004249514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.457803e-7,"about_ca_topic_score_gemma":9.033836e-8,"domain_scores_codex":[0.9979204,0.0000378763,0.0004638895,0.0002676206,0.001048044,0.0002621885],"domain_scores_gemma":[0.9978258,0.0001328065,0.0003595059,0.0004721085,0.0009679746,0.0002418285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000438886,0.0000635977,0.005746847,0.00008194289,0.000009062493,0.000003280478,0.003649236,0.2388574,0.4032784,0.04642419,0.000005114578,0.301837],"study_design_scores_gemma":[0.0003367453,0.0005558439,0.01404241,0.0002058923,0.000002774321,0.00001570824,0.0000317697,0.9625822,0.02166202,0.0003699237,0.00005681137,0.0001379362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4872519,0.0001264123,0.5120692,0.0003551786,0.000114751,0.00004034776,4.456451e-7,0.00002333663,0.00001842427],"genre_scores_gemma":[0.704194,0.00005845057,0.2956319,0.00009292292,0.00001891314,8.601458e-7,1.285423e-7,0.000002712022,7.263373e-8],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7237248,"threshold_uncertainty_score":0.5385832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01175622558245885,"score_gpt":0.2189947644187108,"score_spread":0.2072385388362519,"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."}}