{"id":"W2117541287","doi":"10.1109/icc.2008.413","title":"Throughput Optimization for Hierarchical Cooperation in Ad Hoc Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Throughput; Computer science; Wireless ad hoc network; Scheme (mathematics); Computer network; Scaling; Exponent; Wireless; Cluster (spacecraft); Wireless network; Mobile ad hoc network; Distributed computing; Mathematics; Network packet; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002165126,0.00008890258,0.0001135611,0.00007064134,0.0002588492,0.00006553232,0.0004446677,0.00005587453,0.00004069604],"category_scores_gemma":[0.00005131549,0.00008186237,0.00003297509,0.0004821555,0.0000384776,0.000442455,0.0001504041,0.0001217585,0.000005300535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004248873,"about_ca_system_score_gemma":0.00005694498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.977762e-7,"about_ca_topic_score_gemma":0.00004225334,"domain_scores_codex":[0.9991794,0.00009903454,0.0002202078,0.0002369483,0.00008468295,0.0001797421],"domain_scores_gemma":[0.9992712,0.0001503816,0.00003442945,0.0003766272,0.0001225767,0.00004477649],"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":[0.00002300319,0.0001201245,0.00025555,0.0000030909,0.000006734601,0.000002822196,0.001005634,0.6367478,0.0000557165,0.1844939,0.003734642,0.173551],"study_design_scores_gemma":[0.0004604443,0.00005586421,0.0003454013,0.000008788364,6.522011e-7,0.000006560507,0.000004187664,0.9928519,0.00004512721,0.0001148932,0.005997166,0.0001089967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001340398,0.0008183358,0.9938315,0.002085317,0.0001299669,0.0002979032,2.449207e-7,0.0001135984,0.001382754],"genre_scores_gemma":[0.6467379,0.006852623,0.3444704,0.001280767,0.0000522031,0.00008214825,0.00002376297,0.000008466155,0.0004916506],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6493611,"threshold_uncertainty_score":0.3338251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05149140509389501,"score_gpt":0.2847153561578143,"score_spread":0.2332239510639193,"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."}}