{"id":"W2022161759","doi":"10.1109/wimob.2011.6085344","title":"Selfishness detection for backoff algorithms in wireless networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Exponential backoff; Computer science; Computer network; Node (physics); Selfishness; Distributed coordination function; Set (abstract data type); Carrier sense multiple access with collision avoidance; Wireless; Algorithm; Wireless network; Throughput; IEEE 802.11; Psychology; Telecommunications; Engineering","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":[0.006850617,0.0006107611,0.0008660293,0.00157751,0.001100808,0.001941544,0.001180012,0.001243409,0.0004677563],"category_scores_gemma":[0.05622496,0.000572099,0.0004962263,0.0006871484,0.001827939,0.003300248,0.001563874,0.001962835,0.0001966555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084391,"about_ca_system_score_gemma":0.001118545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006656313,"about_ca_topic_score_gemma":0.0005555477,"domain_scores_codex":[0.9937947,0.002172119,0.0005445709,0.000616663,0.0025177,0.0003542742],"domain_scores_gemma":[0.9634687,0.02509825,0.003934096,0.004233432,0.002739514,0.0005259457],"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":[0.001579483,0.0005031628,0.03133916,0.0003782807,0.00031736,0.0005742873,0.001389302,0.4328973,0.04711426,0.1294336,0.001873455,0.3526004],"study_design_scores_gemma":[0.00002548935,0.0001448727,0.001126483,0.00003651699,0.00002042139,0.0002908834,0.00005180379,0.9648568,0.008861625,0.02388178,0.0006723286,0.00003095653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07407843,0.0005157212,0.9232346,0.0002218669,0.0000557405,0.0001363947,0.00001644189,0.0005675997,0.001173176],"genre_scores_gemma":[0.7935849,0.0002614908,0.205037,0.000125922,0.00006064049,0.0001430444,0.00004258949,0.00005698276,0.0006873854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006850617,"threshold_uncertainty_score":0.03622997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03526938951400849,"score_gpt":0.2457596652214969,"score_spread":0.2104902757074884,"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."}}