{"id":"W2409386829","doi":"10.1109/jsyst.2015.2432674","title":"Energy-Efficient Adaptive Transmission of Scalable Video Streaming in Cognitive Radio Communications","year":2015,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Computer science; Quality of service; Cognitive radio; Energy consumption; Computer network; Scalability; Efficient energy use; Transmission (telecommunications); Real-time computing; Multimedia; Distributed computing; Wireless; Telecommunications","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":[0.001108845,0.000147371,0.0003311571,0.0002888784,0.0001649742,0.0001345972,0.0005641659,0.00007002797,0.000001457892],"category_scores_gemma":[0.00003157642,0.0001302554,0.00008775824,0.0005881701,0.00008613125,0.0002787881,0.00006454736,0.000331376,0.000002235619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000211226,"about_ca_system_score_gemma":0.0002768038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003390966,"about_ca_topic_score_gemma":0.00004775909,"domain_scores_codex":[0.9979581,0.0005142739,0.0005665094,0.0002160129,0.0004332942,0.0003118015],"domain_scores_gemma":[0.9983565,0.0003081058,0.0003190266,0.0003283783,0.000445641,0.0002423108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002700531,0.001193598,0.001923992,0.00005256669,0.0003025167,0.000533778,0.01988715,0.4031399,0.004448103,0.01360223,0.001516614,0.5531295],"study_design_scores_gemma":[0.001153631,0.0001732627,0.0003373949,0.001211793,0.00001520757,0.0006720908,0.0009088255,0.9936407,0.0009375831,0.0003804351,0.000395257,0.0001738787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03734247,0.004532238,0.9527498,0.0001519788,0.0006470924,0.0001393658,0.000003128294,0.00002679253,0.004407102],"genre_scores_gemma":[0.9960226,0.0001477202,0.003592789,0.00001815854,0.0001510571,0.000003955128,9.241498e-7,0.00001076989,0.0000519756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9586802,"threshold_uncertainty_score":0.5311663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04580901378355484,"score_gpt":0.2719102691119515,"score_spread":0.2261012553283967,"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."}}