{"id":"W2027031054","doi":"10.1109/icc.2012.6364002","title":"Competitive pricing for spectrum subleasing for future wireless ad hoc networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Stackelberg competition; Nash equilibrium; Computer science; Operator (biology); Equilibrium point; Interference (communication); Mathematical optimization; Game theory; Mobile network operator; Mathematical economics; Telecommunications; Mathematics; Cellular network; Channel (broadcasting)","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":[0.002480225,0.0009980059,0.0007711852,0.0005326914,0.001234265,0.002264141,0.001438429,0.001385789,0.003766394],"category_scores_gemma":[0.006571334,0.0005279578,0.0008037186,0.0005617108,0.002196472,0.003373719,0.001422746,0.002032769,0.0003401027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003489622,"about_ca_system_score_gemma":0.00233762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767554,"about_ca_topic_score_gemma":0.005693107,"domain_scores_codex":[0.9983214,0.0007792113,0.00003214803,0.0001753613,0.0004743341,0.0002175443],"domain_scores_gemma":[0.9984403,0.000890082,0.0001852529,0.00009383754,0.0002348003,0.0001557426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007272785,0.00007421711,0.0005517813,0.00009919875,0.00003151933,0.0002631766,0.0002068051,0.3801637,0.00265939,0.594163,0.00213958,0.01957488],"study_design_scores_gemma":[0.00001764848,0.00007452783,0.0002181071,0.00001512208,0.00001505289,0.00008640649,0.00007595082,0.8485559,0.0004619507,0.1477131,0.002739591,0.00002665557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05007335,0.001036261,0.9239812,0.00128732,0.0001973059,0.0001194795,0.00004706563,0.00007620405,0.02318189],"genre_scores_gemma":[0.9432576,0.0007966994,0.04994697,0.0001825358,0.000192834,0.0001036195,0.0000296791,0.00003220075,0.005457901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003767554,"threshold_uncertainty_score":0.02531916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007547429882090644,"score_gpt":0.217985564674811,"score_spread":0.2104381347927204,"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."}}