{"id":"W2548939748","doi":"","title":"Performance analysis of Decode-and-Forward cooperative networks with best relay selection","year":2012,"lang":"en","type":"article","venue":"International Conference on Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Relay; Relay channel; Decodes; Computer science; Cooperative diversity; Selection (genetic algorithm); Node (physics); Computer network; Link Access Procedure for Frame Relay; Hop (telecommunications); Topology (electrical circuits); Channel (broadcasting); Decoding methods; Power (physics); Telecommunications; Mathematics; Fading; Engineering; Artificial intelligence","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":[0.0003608234,0.0001373077,0.0002048496,0.0003372634,0.0003151505,0.0001014222,0.001583164,0.00005092116,0.00008673783],"category_scores_gemma":[0.00004014486,0.0001191306,0.00005091598,0.001084331,0.0001700577,0.0006539222,0.0005162571,0.0002813278,0.00001200541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006934106,"about_ca_system_score_gemma":0.00006299878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001749822,"about_ca_topic_score_gemma":0.0002534523,"domain_scores_codex":[0.9989212,0.0001966619,0.0002958284,0.0001867372,0.0002275511,0.0001720274],"domain_scores_gemma":[0.9977867,0.0002616181,0.0001992728,0.001029371,0.0006341455,0.00008890738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000303927,0.0003938952,0.06506189,0.00000254251,0.000786457,9.937378e-8,0.00136952,0.02261347,0.0002494145,0.8792138,0.00008750959,0.03019106],"study_design_scores_gemma":[0.0001784523,0.0001204234,0.03103951,0.00004727983,0.00009778273,0.000004228464,0.00008441843,0.9661322,0.0001397584,0.00001548209,0.001993878,0.0001465702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1661616,0.0007968607,0.7350763,0.006632018,0.0002610258,0.0004078028,0.00001741125,0.0001641845,0.09048278],"genre_scores_gemma":[0.9783692,0.005049757,0.01595852,0.0002301447,0.00002076739,0.0000572934,0.00004770089,0.000006591855,0.0002600449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9435188,"threshold_uncertainty_score":0.4858006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08105159770417639,"score_gpt":0.3338498951524105,"score_spread":0.2527982974482341,"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."}}