{"id":"W2064545165","doi":"10.1007/s11277-011-0249-z","title":"Performance Analysis of Smart Relaying with Equal Gain Combining","year":2011,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Saskatchewan","funders":"","keywords":"Nakagami distribution; Computer science; Fading; Relay; Phase-shift keying; Diversity gain; Keying; Maximal-ratio combining; Focus (optics); Telecommunications; Modulation (music); Diversity combining; Antenna diversity; Cooperative diversity; Outage probability; Diversity (politics); Algorithm; Electronic engineering; Bit error rate; Wireless; Decoding methods; Power (physics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003846673,0.002314555,0.001764285,0.001458585,0.0009391566,0.002930037,0.001430571,0.001826158,0.005361419],"category_scores_gemma":[0.01053798,0.0007426554,0.0008262939,0.001944618,0.002171763,0.002189513,0.001950872,0.0008856927,0.001259889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002354777,"about_ca_system_score_gemma":0.001577771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960753,"about_ca_topic_score_gemma":0.002729103,"domain_scores_codex":[0.9963421,0.001571444,0.0001080179,0.0003775295,0.0009541527,0.0006468248],"domain_scores_gemma":[0.987915,0.008774066,0.0007063437,0.0008526757,0.001573458,0.0001782772],"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":[0.001037444,0.0000727981,0.001872247,0.000302858,0.0002216547,0.0004567507,0.0003287092,0.8232973,0.01507897,0.125488,0.002206543,0.02963667],"study_design_scores_gemma":[0.00004043188,0.000283212,0.0006673202,0.00003395665,0.0001177587,0.0004386988,0.00008875901,0.9687791,0.003557899,0.02495218,0.0009893596,0.00005125458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2092748,0.004076541,0.7174347,0.001848708,0.0001830505,0.0001708566,0.0007077355,0.001155876,0.06514777],"genre_scores_gemma":[0.974875,0.0009853983,0.01958052,0.0001698201,0.0001261651,0.00006709775,0.0001787334,0.00007274341,0.003944492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005361419,"threshold_uncertainty_score":0.02034342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1042585976890252,"score_gpt":0.2889260999706001,"score_spread":0.1846675022815749,"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."}}