{"id":"W2528584088","doi":"10.1109/jsac.2016.2615261","title":"Secure Transmission in Cognitive Satellite Terrestrial Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Satellite Communication Systems","field":"Engineering","cited_by":376,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Channel state information; Telecommunications link; Transmission (telecommunications); Beamforming; Base station; Satellite; Computer network; Interference (communication); Optimization problem; Channel (broadcasting); Telecommunications; Wireless; Algorithm","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":[0.0008235352,0.0006291386,0.0004399862,0.0004317134,0.0005380538,0.0008360365,0.0005461586,0.0005769078,0.0008317747],"category_scores_gemma":[0.002293229,0.0002210681,0.0003581837,0.0007869547,0.001205129,0.000792,0.001084618,0.0004605718,0.0001472698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008765888,"about_ca_system_score_gemma":0.0008537897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003594029,"about_ca_topic_score_gemma":0.003087532,"domain_scores_codex":[0.999335,0.0002135819,0.00001849885,0.00007154003,0.000214534,0.0001468524],"domain_scores_gemma":[0.9989257,0.0007222958,0.0001367011,0.0000697159,0.00011559,0.00002985859],"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":[0.0002208707,0.00003394888,0.001096591,0.0001580008,0.00005449932,0.0004792258,0.0001958408,0.8828745,0.01032563,0.06789309,0.0007580494,0.03590976],"study_design_scores_gemma":[0.00001582446,0.00006131936,0.000227798,0.00001179298,0.00001853494,0.0001021333,0.00006062619,0.9826142,0.002318664,0.01387685,0.0006804869,0.00001179017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1228928,0.00104742,0.8660783,0.0003306956,0.0000482608,0.00003289896,0.00006257826,0.0001750781,0.009332077],"genre_scores_gemma":[0.9814867,0.0005269569,0.01681107,0.00006399056,0.00002654418,0.00002990158,0.00002421462,0.000008217721,0.001022395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003594029,"threshold_uncertainty_score":0.007146239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04276695135308052,"score_gpt":0.294104844381964,"score_spread":0.2513378930288835,"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."}}