{"id":"W2007607403","doi":"10.1109/icassp.2010.5496080","title":"Pareto-optimal solutions of Nash bargaining resource allocation games with spectral mask and total power constraints","year":2010,"lang":"en","type":"article","venue":"","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematical optimization; Bottleneck; Resource allocation; Computer science; Bandwidth (computing); Nash equilibrium; Pareto optimal; Bargaining problem; Pareto principle; Game theory; Computational complexity theory; Multi-objective optimization; Mathematical economics; Mathematics; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001244521,0.00009929541,0.0001596253,0.0001012211,0.0001732714,0.00008608151,0.0002297041,0.00006153867,0.001468763],"category_scores_gemma":[0.0003892907,0.00006892845,0.00003771853,0.0002956244,0.0008589625,0.0001792183,0.00006944563,0.0001754941,0.00005331023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004775008,"about_ca_system_score_gemma":0.00006230974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007765541,"about_ca_topic_score_gemma":0.00004347142,"domain_scores_codex":[0.9987125,0.00006258429,0.0003214636,0.0003082441,0.0003903659,0.000204873],"domain_scores_gemma":[0.9986461,0.000571731,0.0001349483,0.0003955083,0.0001391153,0.0001126345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006175892,0.0001009806,0.006468363,0.000001593144,0.00002556158,0.000001861208,0.002267108,0.0002655163,0.04969407,0.9244561,0.001083515,0.01557363],"study_design_scores_gemma":[0.004580032,0.001565594,0.4515957,0.0001107104,0.0001857248,0.001255892,0.1078949,0.01803675,0.0675578,0.3234683,0.02171131,0.002037307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9066526,0.000009385595,0.02208517,0.0007298065,0.00002693566,0.0001323672,0.0000161332,0.00003530103,0.07031233],"genre_scores_gemma":[0.9893125,5.507693e-7,0.009138467,0.00006831283,0.00002478242,0.000009728301,0.000003357079,0.000006226499,0.0014361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6009877,"threshold_uncertainty_score":0.999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03560089906664556,"score_gpt":0.3068002601224034,"score_spread":0.2711993610557579,"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."}}