{"id":"W2566309962","doi":"10.1002/dac.3247","title":"Resource allocation in heterogeneous cooperative cognitive radio networks","year":2016,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Cognitive radio; Cooperative diversity; Resource allocation; Relay; Computer network; Diversity (politics); Wireless; Channel (broadcasting); Resource (disambiguation); Interference (communication); Wireless network; Constraint (computer-aided design); Harm; Transmission (telecommunications); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001051091,0.0004964917,0.0006450683,0.0004568184,0.0004185225,0.001081858,0.000924782,0.0006485349,0.001172124],"category_scores_gemma":[0.00230343,0.0002559254,0.0004081085,0.0005636702,0.0008447475,0.0008839028,0.0008289819,0.000427088,0.0001952434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128382,"about_ca_system_score_gemma":0.0008410709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006454661,"about_ca_topic_score_gemma":0.004256522,"domain_scores_codex":[0.99925,0.0002716506,0.00001812996,0.0001169677,0.0001718255,0.0001715423],"domain_scores_gemma":[0.9990079,0.0005732875,0.0001229786,0.00008090658,0.0001566576,0.00005837194],"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":[0.00003396327,0.0000255898,0.0002236308,0.00001653417,0.00001662152,0.00007688446,0.00002596087,0.9797084,0.001253827,0.01286121,0.0003353279,0.005422067],"study_design_scores_gemma":[0.00000310408,0.0000141967,0.0000679393,0.000001994086,0.000004274358,0.000009953528,0.00001317694,0.9938368,0.0001422701,0.005741856,0.0001612876,0.000003078872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1219817,0.0007058099,0.8643622,0.0003611704,0.00006191637,0.00005189668,0.00005313781,0.0001458482,0.01227622],"genre_scores_gemma":[0.9894493,0.0001591207,0.008256544,0.0000486604,0.00001890325,0.00003411393,0.00001544546,0.000009992919,0.00200788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006454661,"threshold_uncertainty_score":0.01283413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823933163246986,"score_gpt":0.2698964932296766,"score_spread":0.2516571615972067,"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."}}