{"id":"W4256065040","doi":"10.32920/ryerson.14655603","title":"Resource-Aware Cooperative Caching on Mobile Ad-hoc Peer to Peer Networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Wireless ad hoc network; Computer network; Cache; Mobile ad hoc network; Distributed computing; Vehicular ad hoc network; Overlay network; Software deployment; Ad hoc wireless distribution service; Peer-to-peer; Optimized Link State Routing Protocol; Node (physics); Wireless; Network packet; The Internet; World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001002055,0.0005305748,0.001104359,0.0006776778,0.001101996,0.00104253,0.001414859,0.0007565612,0.0007931523],"category_scores_gemma":[0.003468015,0.0003911669,0.0003775521,0.001057105,0.000612381,0.001744676,0.0008843446,0.0004704066,0.0001997638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002554,"about_ca_system_score_gemma":0.0008938659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009641727,"about_ca_topic_score_gemma":0.00663036,"domain_scores_codex":[0.9992112,0.0002665971,0.00003969575,0.0001199115,0.000261955,0.0001006712],"domain_scores_gemma":[0.9984019,0.0008237931,0.0001072893,0.0002487548,0.0003359531,0.00008229799],"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":[0.0003249205,0.000145128,0.001817736,0.0002257983,0.0001385291,0.0008647847,0.0004768258,0.8431083,0.0161018,0.05085333,0.00416801,0.08177479],"study_design_scores_gemma":[0.00002224227,0.00005260542,0.0002152977,0.000008485568,0.00002388971,0.00008842224,0.00004212136,0.9886687,0.001510191,0.007330416,0.002025072,0.00001255537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2260286,0.004973997,0.754747,0.0006446387,0.0001659078,0.0003312539,0.0001159447,0.001706073,0.01128665],"genre_scores_gemma":[0.9495796,0.001091488,0.0460801,0.00005536556,0.00006791168,0.0001226059,0.00006092012,0.00004014944,0.002901887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009641727,"threshold_uncertainty_score":0.01917124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0228787928486609,"score_gpt":0.2646890071011802,"score_spread":0.2418102142525193,"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."}}