{"id":"W2169948709","doi":"10.1109/lcom.2007.348292","title":"Performance Analysis of Cooperative Diversity Wireless Networks over Nakagami-m Fading Channel","year":2007,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":517,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Nakagami distribution; Fading; Moment-generating function; Probability density function; Signal-to-noise ratio (imaging); Outage probability; Diversity combining; Computer science; Wireless; Channel (broadcasting); Maximal-ratio combining; Bit error rate; Probability of error; Algorithm; Statistics; Mathematics; Wireless network; Topology (electrical circuits); Telecommunications; Combinatorics","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":[0.001648956,0.0008996397,0.0008425624,0.000701785,0.0004860125,0.0009267299,0.0005067927,0.0008496852,0.0005770783],"category_scores_gemma":[0.009592476,0.0002700985,0.0003089707,0.0008335487,0.001182279,0.001056914,0.0008622701,0.0005022187,0.0002052381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391813,"about_ca_system_score_gemma":0.0005725932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002281168,"about_ca_topic_score_gemma":0.001232997,"domain_scores_codex":[0.9988555,0.0004964,0.00003351024,0.000094143,0.0003580665,0.0001624912],"domain_scores_gemma":[0.9934429,0.004856151,0.0006069815,0.0003076857,0.0007078224,0.00007853458],"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":[0.00008389246,0.00001585435,0.00131038,0.00004876186,0.00003300705,0.0001554636,0.0001198421,0.97241,0.005596424,0.01415889,0.0001453397,0.005922121],"study_design_scores_gemma":[0.000004706716,0.00006855534,0.0005282658,0.000009604466,0.00001484278,0.00009361561,0.00003347388,0.9935867,0.001694239,0.003833965,0.0001207697,0.00001139965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.590802,0.002545964,0.3973567,0.0004347806,0.00003414984,0.00003690345,0.00009561187,0.0002699542,0.00842405],"genre_scores_gemma":[0.9952062,0.0004101779,0.003807959,0.0000263052,0.00002109641,0.00001628386,0.00001737269,0.00001163023,0.0004830068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002281168,"threshold_uncertainty_score":0.01009834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04499486000545759,"score_gpt":0.2818834896058828,"score_spread":0.2368886296004252,"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."}}