{"id":"W2990309384","doi":"","title":"Secrecy Analysis of a TAS/MRC Scheme in α-μ Fading Channels.","year":2019,"lang":"en","type":"article","venue":"Wireless Communications and Networking Conference","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Fading; Secrecy; Computer science; Fading distribution; Scheme (mathematics); Maximal-ratio combining; Telecommunications; Computer network; Electronic engineering; Mathematics; Computer security; Channel (broadcasting); Engineering; Rayleigh fading","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":[],"consensus_categories":[],"category_scores_codex":[0.0003593078,0.0001641866,0.0004584759,0.0005001612,0.00006988832,0.00005675184,0.0009924893,0.0001188936,0.00003741001],"category_scores_gemma":[0.000004382123,0.0001908131,0.00006984897,0.001399597,0.0001274574,0.0001554577,0.0004182964,0.0003687833,0.000003557423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004626061,"about_ca_system_score_gemma":0.00002204106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001643092,"about_ca_topic_score_gemma":0.0005664893,"domain_scores_codex":[0.9989291,0.00009596099,0.0004510889,0.000179383,0.0001224604,0.0002220092],"domain_scores_gemma":[0.9977556,0.0002463445,0.0001151399,0.001736329,0.00009595281,0.00005058364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002480438,0.0002857274,0.4667121,0.0003464005,0.001338316,0.000001645243,0.0120076,0.0126417,0.0158589,0.282083,0.00006197616,0.2086378],"study_design_scores_gemma":[0.0001653863,0.00001414742,0.00723988,0.0002805763,0.00005544315,8.569974e-7,0.0002077839,0.9883723,0.0002751785,0.0006995093,0.002466336,0.0002226545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785379,0.004633495,0.00830501,0.0001374176,0.00007891532,0.0002956159,0.000009722639,0.0002793238,0.007722612],"genre_scores_gemma":[0.98495,0.01157055,0.003287113,0.00002013089,0.00001031574,0.00005722327,0.00006359965,0.00002198642,0.00001908154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9757305,"threshold_uncertainty_score":0.7781132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02929363536056067,"score_gpt":0.2615811920801954,"score_spread":0.2322875567196347,"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."}}