{"id":"W2151147819","doi":"10.1109/glocom.1998.775822","title":"A quantitative evaluation of generation methods for correlated Rayleigh random variates","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Random variate; Additive white Gaussian noise; Monte Carlo method; Computer science; White noise; Control variates; Algorithm; Random number generation; Statistics; Mathematics; Random variable; Hybrid Monte Carlo","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":[0.000887477,0.00007905294,0.0001501034,0.00008262182,0.00003446403,0.000007342143,0.00009229782,0.00006066807,0.000200543],"category_scores_gemma":[0.0003386004,0.00007611294,0.00004177148,0.0001516045,0.00001883221,0.0001476885,0.000009925097,0.00005303053,0.000003855858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005030749,"about_ca_system_score_gemma":0.000004398863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003233881,"about_ca_topic_score_gemma":0.000003546364,"domain_scores_codex":[0.9992975,0.0001843271,0.0002642449,0.00008110622,0.0000984326,0.00007440471],"domain_scores_gemma":[0.9989153,0.0004439746,0.00006225302,0.0002258566,0.0003372005,0.0000153877],"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":[0.00002433828,0.00004652545,0.000006233322,0.00002899853,0.00009284692,1.620461e-8,0.0006936315,0.2312754,0.3975808,0.02380669,0.001273997,0.3451705],"study_design_scores_gemma":[0.0007500892,0.00003160379,0.000008255165,0.000007148253,0.00003270634,2.399346e-7,0.00002344474,0.7583186,0.2379824,0.002486569,0.0002937098,0.00006519867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003367732,0.001520898,0.9891112,0.00002719731,0.00008115087,0.0006335292,0.000003392306,0.0003225874,0.004932357],"genre_scores_gemma":[0.3983082,0.0001939518,0.6011589,0.000005889075,0.000006937878,0.0002214679,0.00002165456,0.00001428507,0.00006877004],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5270432,"threshold_uncertainty_score":0.3103796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.162184865323168,"score_gpt":0.4155855942500112,"score_spread":0.2534007289268432,"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."}}