{"id":"W2152484151","doi":"10.1109/t-wc.2008.071465","title":"Joint rate and power allocation for cognitive radios in dynamic spectrum access environment","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":271,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cognitive radio; Computer science; Quality of service; Interference (communication); Throughput; Channel (broadcasting); Constraint (computer-aided design); Transmitter power output; Computer network; Fading; Power control; Mathematical optimization; Telecommunications; Wireless; Power (physics); Transmitter; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002365271,0.0001901742,0.0002292326,0.0002721474,0.0006876529,0.00009980441,0.0006022313,0.00007383888,0.000008892852],"category_scores_gemma":[0.000005901943,0.0002105241,0.00008565703,0.0003574372,0.0002381378,0.0005062511,0.00002037519,0.0003235448,0.000009914485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000172919,"about_ca_system_score_gemma":0.00006675387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005787742,"about_ca_topic_score_gemma":0.0004343791,"domain_scores_codex":[0.9986617,0.0001962246,0.0003288909,0.0003991974,0.0001304181,0.0002835513],"domain_scores_gemma":[0.998319,0.0005690907,0.0001036867,0.0008714756,0.00004765356,0.00008910132],"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":[0.0007241287,0.00971099,0.0007843398,0.0001626976,0.001070853,0.0001156571,0.02988191,0.1279179,0.0207581,0.03713388,0.0002728021,0.7714667],"study_design_scores_gemma":[0.001828067,0.000217498,0.01535797,0.0001647272,0.00003711721,0.00009623719,0.0001649283,0.9727698,0.007039593,0.001600654,0.0002235622,0.0004998501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08966247,0.0002018518,0.9052782,0.003844599,0.000109364,0.0006530075,0.00002093525,0.00008082938,0.0001487515],"genre_scores_gemma":[0.9919053,0.003626342,0.003922105,0.0002475113,0.000008098765,0.0001898555,0.00001118649,0.00002093533,0.0000686539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9022428,"threshold_uncertainty_score":0.8584925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03278684844093369,"score_gpt":0.2668270306243564,"score_spread":0.2340401821834227,"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."}}