{"id":"W4389331917","doi":"10.1109/twc.2023.3336535","title":"Learning-Based Reliable and Secure Transmission for UAV-RIS-Assisted Communication Systems","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Singapore University of Technology and Design; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Fujian Province; National Natural Science Foundation of China","keywords":"Computer science; Eavesdropping; Beamforming; Artificial noise; Jamming; Quality of service; Secure transmission; Computer network; Channel state information; Transmission (telecommunications); Channel (broadcasting); Secrecy; Real-time computing; Wireless; Telecommunications; Computer security; Transmitter","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":[0.0004293497,0.000622229,0.0004966598,0.0002300086,0.0003312452,0.0004238288,0.0007991422,0.0005485689,0.000854624],"category_scores_gemma":[0.00107634,0.000238219,0.0003091004,0.000287418,0.0005919314,0.000863412,0.0008001553,0.0007296983,0.0002121073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004661252,"about_ca_system_score_gemma":0.0006430126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002139693,"about_ca_topic_score_gemma":0.002404519,"domain_scores_codex":[0.9996283,0.00008364098,0.00001746582,0.00008976166,0.0001213789,0.00005935679],"domain_scores_gemma":[0.9996505,0.0001430749,0.00007212278,0.00003671088,0.00007847003,0.00001920747],"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":[0.0001066916,0.00005649247,0.0008599993,0.00006979555,0.00002991855,0.000124944,0.00009393603,0.8721909,0.01459905,0.008102265,0.0008155737,0.1029505],"study_design_scores_gemma":[0.000004227511,0.0000416367,0.00006853481,0.000002197856,0.000004148361,0.00001891501,0.000005124057,0.997465,0.001245158,0.0009601491,0.0001815014,0.000003350816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02746135,0.0002046613,0.9701571,0.0001227847,0.00002890916,0.00002127419,0.00001765214,0.0001947723,0.00179147],"genre_scores_gemma":[0.9503547,0.0001796,0.04735923,0.00008972258,0.0000290884,0.00005016243,0.00003841563,0.00001646543,0.001882643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002139693,"threshold_uncertainty_score":0.00425446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02656916239155742,"score_gpt":0.2671756503578226,"score_spread":0.2406064879662652,"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."}}