{"id":"W1985708909","doi":"10.1109/mobhoc.2006.278559","title":"Max-Min Fair Capacity of Wireless Mesh Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Wireless mesh network; Computer network; Fairness measure; Bandwidth (computing); Network topology; Wireless network; Context (archaeology); Wireless; Protocol (science); Distributed computing; Max-min fairness; Collision; Mathematical optimization; Resource allocation; Telecommunications; Mathematics; Throughput; Computer security","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":[0.006858417,0.0007722397,0.0009035118,0.001473583,0.001260331,0.002786224,0.002368439,0.0007829951,0.002527644],"category_scores_gemma":[0.01894522,0.0004977211,0.0005288994,0.001565848,0.002863896,0.004856823,0.00175964,0.001167986,0.0003472957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003515281,"about_ca_system_score_gemma":0.002795829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002669811,"about_ca_topic_score_gemma":0.001732527,"domain_scores_codex":[0.9970177,0.001277677,0.000109148,0.0003807709,0.0007988758,0.0004157557],"domain_scores_gemma":[0.9918315,0.006066103,0.0003648041,0.0008080872,0.0007468868,0.0001826442],"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":[0.00019295,0.00003572309,0.0005583732,0.0001447044,0.00003801582,0.00006186522,0.000175513,0.5508887,0.002215163,0.4004549,0.002227325,0.04300677],"study_design_scores_gemma":[0.000007250415,0.00001692447,0.0001152739,0.00002408538,0.000007880676,0.00002825979,0.00002073282,0.8482294,0.001836166,0.1476788,0.00201899,0.00001630998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01746812,0.001535732,0.9721942,0.0004059721,0.0001224016,0.00006286409,0.0001291809,0.0004011618,0.007680265],"genre_scores_gemma":[0.8545865,0.001167546,0.138545,0.00016809,0.000192751,0.0003236887,0.0001711765,0.0001994953,0.004645769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006858417,"threshold_uncertainty_score":0.03627121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042560144981236,"score_gpt":0.2038039264624128,"score_spread":0.1933783250126004,"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."}}