{"id":"W2056404676","doi":"10.1109/tcomm.2014.2363116","title":"Two-Stage Spectrum Sharing With Combinatorial Auction and Stackelberg Game in Recall-Based Cognitive Radio Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stackelberg competition; Cognitive radio; Computer science; Frequency allocation; Resource allocation; Quality of service; Computer network; Game theory; Scheme (mathematics); Mathematical optimization; Telecommunications; Mathematics; Mathematical economics","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":[0.0004517653,0.0002331167,0.0002652687,0.0002932838,0.0005051178,0.0002337709,0.0006288044,0.00009165047,0.00001126871],"category_scores_gemma":[0.00001068875,0.0002404145,0.00006491209,0.0008250487,0.0002278741,0.000400538,0.00001664528,0.0007593332,0.000005768974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001461317,"about_ca_system_score_gemma":0.00006322785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003179228,"about_ca_topic_score_gemma":0.003725428,"domain_scores_codex":[0.9982905,0.0003337478,0.0003122024,0.0004920714,0.0002073033,0.0003642227],"domain_scores_gemma":[0.9976017,0.0008813541,0.0001192577,0.001173025,0.0000927002,0.0001319479],"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":[0.0007325167,0.002214625,0.001856293,0.00004382376,0.0002865801,0.00003099506,0.00235637,0.6875405,0.0001987567,0.136317,0.00003411389,0.1683884],"study_design_scores_gemma":[0.00275738,0.0002945683,0.001713643,0.0002088834,0.00003559412,0.00002064272,0.00006525795,0.9922716,0.0004700297,0.001545915,0.0002943156,0.0003221871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02082176,0.00008909821,0.9750208,0.001433016,0.0003635757,0.0003584619,0.000005441391,0.0001866742,0.001721213],"genre_scores_gemma":[0.9942854,0.0001839429,0.005122816,0.000183637,0.00006679838,0.00005224768,0.00000830608,0.00002704814,0.00006978411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9734637,"threshold_uncertainty_score":0.9803817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01797779602636141,"score_gpt":0.2538957680653826,"score_spread":0.2359179720390212,"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."}}