{"id":"W1484912939","doi":"10.1109/pacrim.2001.953644","title":"Moment-based estimation of the Nakagami-m fading parameter","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Estimator; Fading; Moment (physics); Nakagami distribution; Estimation theory; Mathematics; Computer science; Statistics; Applied mathematics; Consistent estimator; Algorithm; Minimum-variance unbiased estimator; Physics","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":[0.00003047694,0.00005060861,0.0000567003,0.0000327816,0.00002251697,0.000005143374,0.0001666321,0.0000245526,0.0001089637],"category_scores_gemma":[0.00001820202,0.0000383171,0.00002877389,0.0001149137,0.00002322644,0.00006990525,0.00001879873,0.00006004086,0.000009031097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003050956,"about_ca_system_score_gemma":9.374645e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000196581,"about_ca_topic_score_gemma":8.584254e-7,"domain_scores_codex":[0.9996955,0.00001188521,0.0001210205,0.00003926913,0.00006965233,0.00006271465],"domain_scores_gemma":[0.9995273,0.00006169001,0.00002411418,0.0003634812,0.00001281886,0.00001061394],"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":[5.901226e-7,0.00002418028,0.0002348662,0.00004063861,0.000009894198,7.564993e-8,0.0001221604,0.8837487,0.01252533,0.003149515,0.00112057,0.09902355],"study_design_scores_gemma":[0.00004451663,0.0000033301,0.0001467763,0.00001579072,0.000001755522,1.654516e-7,0.000004407292,0.7638829,0.2350207,0.0003491082,0.0004918638,0.00003872733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05736791,0.000100005,0.9337749,0.000152565,0.00003127728,0.0001326241,0.000001319045,0.0004964151,0.007943027],"genre_scores_gemma":[0.9294387,0.00001750409,0.07035775,0.00003843302,0.000002036917,0.00002012542,8.570227e-7,0.00001051377,0.0001140787],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8720708,"threshold_uncertainty_score":0.1562526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880424448530073,"score_gpt":0.230507046113566,"score_spread":0.2117028016282653,"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."}}