{"id":"W2069509565","doi":"10.1109/chinacom.2007.4469341","title":"Fair Adaptive Resource Allocation for Multiuser OFDM Cognitive Radio Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Resource allocation; Throughput; Transmitter power output; Computer network; Resource management (computing); Interference (communication); Constraint (computer-aided design); Radio resource management; Real-time computing; Telecommunications; Transmitter; Wireless; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001844303,0.0001375204,0.0001377437,0.00007763509,0.00005641724,0.00001699662,0.00006135788,0.0000960848,0.000006821513],"category_scores_gemma":[0.00003713577,0.0001423215,0.00003418477,0.0001743778,0.00002056329,0.0001741863,0.000008987916,0.00007758651,0.00001546824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000120656,"about_ca_system_score_gemma":0.000005898404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000723148,"about_ca_topic_score_gemma":0.00002339345,"domain_scores_codex":[0.999224,0.00001186428,0.0002271021,0.0001676537,0.0001062857,0.0002630622],"domain_scores_gemma":[0.9993601,0.0002982504,0.0000407106,0.0001054612,0.0001321094,0.00006331645],"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":[0.00006267281,0.0000108892,0.0000375457,0.00002964428,0.00003847213,9.853505e-7,0.0002578523,0.9890271,0.0003041594,0.002190439,0.001044988,0.006995267],"study_design_scores_gemma":[0.0006675826,0.00004021462,0.000216869,0.00006592881,0.00001812485,0.000002640792,0.001229637,0.9903408,0.003428225,0.00002585703,0.003757966,0.0002061007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003979343,0.0002939198,0.9878306,0.000009078873,0.0002194584,0.0007641097,0.000009477143,0.0005417438,0.006352207],"genre_scores_gemma":[0.9728897,0.00002002567,0.0257953,0.00002759443,0.0002377911,0.00008753393,0.00008602098,0.00006140774,0.0007945984],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9689104,"threshold_uncertainty_score":0.5803702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257009105345925,"score_gpt":0.2285166327299558,"score_spread":0.2159465416764966,"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."}}