{"id":"W2740877105","doi":"10.1109/icc.2017.7996705","title":"Collaborative hierarchical caching for traffic offloading in heterogeneous networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Heterogeneous network; Computer network; Cache; Network topology; Distributed computing; TRACE (psycholinguistics); Cellular network; Wireless network; Wireless","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":[0.0006718666,0.0005910536,0.0009130617,0.0004118504,0.000681549,0.000741123,0.001006834,0.000736083,0.0007954464],"category_scores_gemma":[0.001466909,0.0002829212,0.0005312428,0.0006600152,0.0006366222,0.00107793,0.0007931545,0.0005308209,0.0001249771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001318146,"about_ca_system_score_gemma":0.001003787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008001015,"about_ca_topic_score_gemma":0.01175718,"domain_scores_codex":[0.9995483,0.000143994,0.000016246,0.00008024244,0.0001012761,0.0001099809],"domain_scores_gemma":[0.9993727,0.0003490827,0.00006464493,0.00009550886,0.00007523858,0.00004281514],"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":[0.00004897008,0.0000457253,0.0004736791,0.00003944723,0.00002386416,0.0001152302,0.00004552615,0.9599279,0.006276967,0.01512427,0.0005866269,0.01729186],"study_design_scores_gemma":[0.000003162574,0.00000739871,0.00005987657,9.131749e-7,0.000003994789,0.000008984358,0.000006763478,0.9969732,0.0003676655,0.002451658,0.000114004,0.000002388186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05952516,0.0003024811,0.93706,0.0001142085,0.00002476453,0.00005288983,0.00004002425,0.0002557747,0.002624792],"genre_scores_gemma":[0.955852,0.0001429146,0.04295992,0.00004147066,0.0000190936,0.00005457364,0.00004522524,0.0000240634,0.0008607656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008001015,"threshold_uncertainty_score":0.0159089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699510514730616,"score_gpt":0.2667523258704803,"score_spread":0.2497572207231741,"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."}}