{"id":"W2091738552","doi":"10.1109/vtcfall.2014.6966000","title":"Hybrid-Optimization-Based Power Allocation for Cognitive Relay Transmission","year":2014,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rayleigh fading; Relay; Computer science; Fading; Interference (communication); Transmission (telecommunications); Cognitive radio; Power (physics); Mathematical optimization; Telecommunications; Channel (broadcasting); Wireless; Mathematics","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":[0.0006596008,0.0006567786,0.0006174486,0.0003086657,0.0002505711,0.0007223461,0.0006742165,0.0004904767,0.0009038571],"category_scores_gemma":[0.001229771,0.0002742619,0.0003661308,0.0005231941,0.0005844752,0.0006968775,0.0005601651,0.0003782688,0.0001529663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006664803,"about_ca_system_score_gemma":0.0006562117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001960278,"about_ca_topic_score_gemma":0.00196097,"domain_scores_codex":[0.9996173,0.0001450909,0.00001300016,0.00006168855,0.00009516915,0.0000676358],"domain_scores_gemma":[0.9996306,0.0002329532,0.0000480681,0.00001861672,0.00005676158,0.00001312178],"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":[0.00005650202,0.00002783386,0.000188984,0.0000568539,0.00003767279,0.00006362297,0.00004415338,0.9637938,0.002846051,0.01541751,0.0004235393,0.01704351],"study_design_scores_gemma":[0.000004713103,0.0000188306,0.00004668051,0.000002032256,0.00000573986,0.0000171251,0.0000065188,0.9968279,0.0003174523,0.002624009,0.0001259903,0.000003134688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02981304,0.0005740285,0.9649549,0.0001274729,0.0000223934,0.00002966022,0.00001638474,0.00008286378,0.004379294],"genre_scores_gemma":[0.9522065,0.0003120667,0.04559052,0.0000642757,0.00002615303,0.00006652506,0.00001524572,0.000021611,0.001697082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001960278,"threshold_uncertainty_score":0.004835725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159641763817679,"score_gpt":0.268157598780582,"score_spread":0.2465611811424052,"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."}}