{"id":"W2164974156","doi":"10.1109/vetecs.2005.1543246","title":"A Simple Efficient Method for Generating Independent Nakagami-m Fading Samples","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Nakagami distribution; Fading; Fading distribution; Simple (philosophy); Computer science; Wireless; Envelope (radar); Algorithm; Mathematics; Electronic engineering; Telecommunications; Engineering; Rayleigh fading; Decoding methods","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":[0.0002622557,0.0001335205,0.0001501429,0.00008738709,0.0001135179,0.0000342015,0.0002327063,0.00006074377,0.00005000356],"category_scores_gemma":[0.00005279198,0.0001348352,0.00005979061,0.0001014737,0.000009718679,0.0000867429,0.00006774541,0.0001141655,0.00000771436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001346577,"about_ca_system_score_gemma":0.000007698232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009804883,"about_ca_topic_score_gemma":0.00005869365,"domain_scores_codex":[0.999218,0.0000230778,0.0002650764,0.0001510704,0.0001057405,0.0002370568],"domain_scores_gemma":[0.9992658,0.0002383172,0.00003430305,0.0003634501,0.00004754711,0.00005053355],"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":[0.000001758656,0.00001202451,0.00001670147,0.00002022096,0.00001000925,8.498287e-8,0.0001616972,0.8138174,0.0623563,0.006275641,0.0004315757,0.1168966],"study_design_scores_gemma":[0.0001254996,0.000009465436,0.00001824296,0.000007768042,0.000003780975,0.000001727462,0.00006979083,0.7407724,0.2373633,0.0003525426,0.02113896,0.0001365955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01415235,0.0002864031,0.9823219,0.00005999668,0.00003191829,0.000316747,0.000009536389,0.001234174,0.001587022],"genre_scores_gemma":[0.4663213,0.00002197891,0.5333347,0.00006734685,0.00005136293,0.000120296,0.00001067513,0.00002756315,0.00004474723],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.452169,"threshold_uncertainty_score":0.5498422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02808681952564738,"score_gpt":0.3184123046800185,"score_spread":0.2903254851543711,"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."}}