{"id":"W2492119979","doi":"10.1109/tvt.2015.2454234","title":"Repeated Game Analysis for Cooperative MAC With Incentive Design for Wireless Networks","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless; Incentive; Computer network; Computer science; Game theory; Wireless network; Telecommunications; Economics; Microeconomics","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":[0.0003866176,0.000221885,0.0003709718,0.0005652843,0.000338464,0.00008328666,0.0007823135,0.0002144293,0.000004015264],"category_scores_gemma":[0.0000171769,0.0001912757,0.0001388559,0.002820449,0.0001653265,0.0002012868,0.000009115587,0.0002946919,0.000003723928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141543,"about_ca_system_score_gemma":0.0001230716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003893882,"about_ca_topic_score_gemma":0.0001130469,"domain_scores_codex":[0.9985585,0.0001598037,0.0002685163,0.0005321598,0.0001420461,0.0003389658],"domain_scores_gemma":[0.9977989,0.0002378309,0.0001182082,0.000867504,0.0008815964,0.00009594097],"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":[0.0002334964,0.0002213577,0.00002780454,0.000004069973,0.0009507882,0.000005448117,0.0003752882,0.9427517,0.0005594363,0.009703453,0.0001851719,0.044982],"study_design_scores_gemma":[0.001372865,0.00084273,0.00000934114,0.00002385372,0.0002082256,0.00000769045,0.0001044078,0.9686151,0.02676594,0.0003125813,0.00147436,0.000262862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00441213,0.0001862392,0.9919358,0.001733571,0.0001307828,0.00111842,0.00001118227,0.0004532163,0.00001858333],"genre_scores_gemma":[0.9282731,0.0001216761,0.07023964,0.0001999572,0.00001299425,0.0009752905,0.00001215396,0.00001923117,0.0001459471],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.923861,"threshold_uncertainty_score":0.7799998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04736447180152522,"score_gpt":0.276572141559699,"score_spread":0.2292076697581738,"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."}}