{"id":"W4245779315","doi":"10.1002/ett.1385","title":"Improved OFDMA uplink transmission <i>via</i> cooperative relaying in the presence of frequency offsets—Part II: Outage information rate analysis","year":2009,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta","funders":"","keywords":"Telecommunications link; Relay; Diversity gain; Computer science; Node (physics); Computer network; Orthogonal frequency-division multiplexing; Transmission (telecommunications); Interference (communication); Electronic engineering; Ergodic theory; Orthogonal frequency-division multiple access; Fading; Telecommunications; Engineering; Mathematics; Power (physics); Channel (broadcasting); 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":[0.001718637,0.0006942939,0.0009541038,0.000485425,0.0004228105,0.0009505996,0.000590983,0.0005706109,0.00104181],"category_scores_gemma":[0.004326849,0.0002370867,0.0003985623,0.000660829,0.000862072,0.0008251553,0.0007042976,0.0004784568,0.0003099632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008456882,"about_ca_system_score_gemma":0.0005704214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001732406,"about_ca_topic_score_gemma":0.001102098,"domain_scores_codex":[0.9990898,0.0003060709,0.00004055718,0.00007733129,0.0003645037,0.0001217509],"domain_scores_gemma":[0.9977739,0.001212182,0.0003480076,0.0002598001,0.0003680449,0.00003796629],"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":[0.0002610085,0.0000710836,0.00200921,0.0003360428,0.0001061588,0.001304529,0.0005611634,0.8406987,0.03936273,0.05821811,0.002321952,0.05474928],"study_design_scores_gemma":[0.000009814022,0.00008540653,0.000578429,0.00002442105,0.00005112152,0.0005193573,0.00005464688,0.9863185,0.007060552,0.004389025,0.0008860634,0.00002275752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1773405,0.002201357,0.8045523,0.0003795739,0.00006940754,0.00005431157,0.0001167517,0.0004586178,0.01482723],"genre_scores_gemma":[0.9719045,0.0007175161,0.02614206,0.00004492958,0.00005073594,0.00002745081,0.0000494165,0.00003104918,0.001032274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001732406,"threshold_uncertainty_score":0.009089172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122515768203092,"score_gpt":0.256209461534068,"score_spread":0.2349843038520371,"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."}}