{"id":"W2540542001","doi":"10.1002/9780470579398.ch5","title":"Cross‐Layer Design Framework for Adaptive Cooperative Caching in Mobile Ad Hoc Networks","year":2010,"lang":"en","type":"other","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Mobile ad hoc network; Computer science; Computer network; Layer (electronics); Adaptive quality of service multi-hop routing; Wireless ad hoc network; Distributed computing; Optimized Link State Routing Protocol; Telecommunications; Wireless; Chemistry; Network packet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004672752,0.0004095597,0.0004757376,0.0002487595,0.000138115,0.0003829012,0.001070203,0.0008251889,0.0002850711],"category_scores_gemma":[0.00006058429,0.0003523003,0.0001569021,0.0002662595,0.00007142811,0.00019605,0.0001781654,0.001245521,0.00004694885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006696614,"about_ca_system_score_gemma":0.0001259017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001537714,"about_ca_topic_score_gemma":0.0007518413,"domain_scores_codex":[0.9980164,0.0001511503,0.0002860531,0.0008301626,0.0002066522,0.0005096338],"domain_scores_gemma":[0.9982255,0.0006618842,0.0001779487,0.0007361199,0.0000895353,0.0001090808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004198155,0.0005478056,0.0001313604,0.00007546013,0.0005063658,0.0001447447,0.003364213,0.1459331,0.0002155139,0.0970858,0.3190342,0.4325415],"study_design_scores_gemma":[0.001302965,0.0007143861,0.00002579019,0.000832256,0.0000299585,0.00001296281,0.0001116425,0.6735233,0.00008631595,0.002495127,0.3193422,0.001523161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0000341456,0.006657275,0.9673799,0.00003848848,0.001438584,0.001195893,0.00001433772,0.000390895,0.02285049],"genre_scores_gemma":[0.009538729,0.001015709,0.4201852,0.001308601,0.0008631594,0.0009530375,0.00001974866,0.0004615761,0.5656542],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5471947,"threshold_uncertainty_score":0.9998929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03473326091010108,"score_gpt":0.2895917388760803,"score_spread":0.2548584779659792,"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."}}