{"id":"W3031131253","doi":"10.1007/s11277-020-07488-8","title":"Performance Analysis in Double-Rayleigh Channels with Diversity Combining Techniques","year":2020,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Cumulative distribution function; Ergodic theory; Computer science; Maximal-ratio combining; Probability density function; Monte Carlo method; Applied mathematics; Expression (computer science); Function (biology); Diversity combining; Algorithm; Statistical physics; Mathematics; Statistics; Physics; Mathematical analysis","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":[0.001605117,0.001999528,0.001186348,0.001214675,0.0007135848,0.00197267,0.0007855817,0.001101085,0.004175593],"category_scores_gemma":[0.005387873,0.0004623761,0.0006838551,0.001825278,0.001091081,0.001474939,0.00190533,0.0007830152,0.001014113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355315,"about_ca_system_score_gemma":0.001126599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002543579,"about_ca_topic_score_gemma":0.003219921,"domain_scores_codex":[0.9978472,0.0006479589,0.00006049282,0.0001938626,0.0006416736,0.0006088616],"domain_scores_gemma":[0.994149,0.00393483,0.0003315211,0.0003755268,0.001069026,0.0001402563],"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":[0.00141089,0.0001509873,0.004245551,0.0005000014,0.0002654867,0.0007822964,0.0003213691,0.8394233,0.04569541,0.04817422,0.001972885,0.05705753],"study_design_scores_gemma":[0.0000251829,0.0002722958,0.001444794,0.00004384375,0.0000911934,0.0005237978,0.0001121364,0.9801445,0.0096405,0.006765421,0.0008887806,0.00004756023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3936961,0.005657739,0.5523891,0.0008422641,0.0001643793,0.0001010312,0.0006186649,0.0008316377,0.04569914],"genre_scores_gemma":[0.974052,0.001303855,0.02040378,0.0001055041,0.0001108058,0.00004418808,0.0001820904,0.00007122986,0.003726624],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004175593,"threshold_uncertainty_score":0.01396877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04381667901249033,"score_gpt":0.2473644430603871,"score_spread":0.2035477640478968,"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."}}