{"id":"W2888015138","doi":"10.1002/ett.3502","title":"Subcarriers assignment scheme for multiple secondary users in OFDMA‐based IEEE 802.22 WRAN: A game theoretic approach","year":2018,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Orthogonal frequency-division multiple access; Computer science; Channel (broadcasting); Benchmark (surveying); Mathematical optimization; Cournot competition; Orthogonal frequency-division multiplexing; Nash equilibrium; Cognitive radio; Computer network; Transmitter power output; Wireless; Telecommunications; Mathematics; Transmitter","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002066737,0.0003076595,0.0002888443,0.0006946549,0.0003757897,0.00003625198,0.0008162046,0.0002674659,0.0000495095],"category_scores_gemma":[0.00005340473,0.0003453414,0.000114392,0.001172143,0.0004471516,0.0002458252,0.00001310616,0.0006583904,0.000007797209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003432545,"about_ca_system_score_gemma":0.0000489941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001003124,"about_ca_topic_score_gemma":0.00007541988,"domain_scores_codex":[0.9985315,0.00005413499,0.0004532239,0.0003434865,0.0001461719,0.0004715419],"domain_scores_gemma":[0.9981394,0.0003214159,0.00008765048,0.001315164,0.00009712837,0.00003917951],"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":[0.00003969486,0.0001612944,0.0001002996,0.00006112722,0.0000641671,1.774342e-7,0.0002721203,0.9590698,0.002197611,0.0006449858,0.0001264477,0.03726223],"study_design_scores_gemma":[0.0009894674,0.00009124618,0.00006012409,0.00009194356,0.00003124272,0.000001138854,0.001417197,0.9634013,0.03088589,0.0008059198,0.00183327,0.0003913185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01682913,0.000401296,0.9771566,0.0007458474,0.0001692965,0.0009234757,0.00005228084,0.003102649,0.0006194539],"genre_scores_gemma":[0.7418033,0.0007965626,0.2555327,0.00002602084,0.00001091634,0.001695722,0.00003922142,0.00007326926,0.00002224421],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7249742,"threshold_uncertainty_score":0.9998999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578923737834627,"score_gpt":0.2489351444679431,"score_spread":0.2331459070895969,"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."}}