{"id":"W2142402258","doi":"10.1109/lcomm.2013.090213.131493","title":"Opportunistic Cooperative Communication in the Presence of Co-Channel Interferences and Outdated Channel Information","year":2013,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Channel state information; Computer science; Channel (broadcasting); Interference (communication); Co-channel interference; Cooperative diversity; Signal-to-noise ratio (imaging); Energy (signal processing); Coding (social sciences); Fading; Diversity scheme; Telecommunications; Probability of error; Maximal-ratio combining; Topology (electrical circuits); Algorithm; Mathematics; Wireless; Statistics","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":[0.002309183,0.0006779162,0.000824607,0.0005369823,0.0006961859,0.001124328,0.000762776,0.0007930162,0.0002369748],"category_scores_gemma":[0.0110296,0.0004006865,0.0002284914,0.0008293205,0.001235752,0.001645727,0.001471852,0.0005043098,0.00008716538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006943141,"about_ca_system_score_gemma":0.0009578482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002400498,"about_ca_topic_score_gemma":0.003526202,"domain_scores_codex":[0.998602,0.0005077063,0.00004791097,0.0001429591,0.0003579795,0.000341579],"domain_scores_gemma":[0.9860981,0.01093894,0.001238228,0.0007371237,0.0007966036,0.0001910221],"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":[0.000444137,0.00007235853,0.005598589,0.0001348197,0.0001102667,0.001915689,0.000832387,0.9130713,0.01430368,0.03085399,0.0005110402,0.03215164],"study_design_scores_gemma":[0.00001786142,0.0001303413,0.001069192,0.00001082221,0.00004022687,0.0005289864,0.0002353096,0.9794939,0.00412845,0.01376398,0.0005572072,0.00002370176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5512187,0.0007647427,0.4412692,0.0002799717,0.00003710128,0.00004063773,0.00005948397,0.0001492315,0.006180755],"genre_scores_gemma":[0.9940642,0.0001686166,0.005273114,0.00002562319,0.00001407633,0.00001256,0.000009971835,0.000006221295,0.0004256685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002400498,"threshold_uncertainty_score":0.01221228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0674425059535089,"score_gpt":0.2957908105889762,"score_spread":0.2283483046354673,"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."}}