{"id":"W2067358804","doi":"10.1109/tetc.2014.2367415","title":"A Cross-Layer Secure Communication Model Based on Discrete Fractional Fourier Fransform (DFRFT)","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Emerging Topics in Computing","topic":"Mathematical Analysis and Transform Methods","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Fractional Fourier transform; Computer science; Communication source; Discrete Fourier transform (general); Generalization; SIGNAL (programming language); Fourier transform; Channel (broadcasting); Theoretical computer science; Algorithm; Computer network; Mathematics; Fourier analysis; Mathematical analysis","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":[0.001572274,0.0002789439,0.0004140196,0.0002810413,0.0004951479,0.00008562674,0.0002878799,0.0001791397,0.0002178492],"category_scores_gemma":[0.00009040639,0.0002524244,0.0003000126,0.0003480315,0.00007303039,0.0001422825,0.000003463397,0.0008434947,0.00001124101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001064386,"about_ca_system_score_gemma":0.00003633866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002764934,"about_ca_topic_score_gemma":0.00007374688,"domain_scores_codex":[0.99779,0.000221729,0.0007265727,0.000376144,0.0005305925,0.0003549108],"domain_scores_gemma":[0.9975569,0.001421341,0.0001519973,0.0006762188,0.00009940149,0.00009410151],"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":[0.00005058815,0.0004662507,0.0001017985,0.0001828964,0.00005894238,0.000001165552,0.0009137685,0.9005848,0.00003498662,0.05770218,0.0000315173,0.03987106],"study_design_scores_gemma":[0.0006476415,0.00004594496,0.00005388695,0.000231385,0.00005061861,0.000001401047,0.00003301524,0.8918559,0.0009820956,0.1054644,0.0003916973,0.0002419904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03093315,0.000005717009,0.9581766,0.001191508,0.000182871,0.0002245515,0.00000836531,0.0001213448,0.009155884],"genre_scores_gemma":[0.7955124,0.000006402339,0.2037013,0.0002969269,0.00007145213,0.00002197653,0.000003655588,0.00003406573,0.0003518499],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7645792,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05596229041425209,"score_gpt":0.3827187010038526,"score_spread":0.3267564105896005,"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."}}