{"id":"W4297802369","doi":"10.1109/iccworkshops53468.2022.9882165","title":"Dynamic Caching in a Hybrid Millimeter-wave/Microwave C-RAN","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Communications Workshops (ICC Workshops)","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Radio access network; Cache; Markov decision process; Computer network; Latency (audio); Cloud computing; Wireless; Optimization problem; Wireless network; Cellular network; Access network; Markov chain; Markov process; Distributed computing; Base station; Telecommunications; Algorithm","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","open_science"],"consensus_categories":[],"category_scores_codex":[0.001222379,0.000420977,0.0004101895,0.0009891092,0.0009996853,0.0006113922,0.007294096,0.00009103384,0.0004221074],"category_scores_gemma":[0.0001224879,0.0004992378,0.0002779898,0.001180596,0.0001639092,0.0006451023,0.002292303,0.002285377,0.00009774022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009290212,"about_ca_system_score_gemma":0.0002274109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001779448,"about_ca_topic_score_gemma":0.0005922564,"domain_scores_codex":[0.9957179,0.0008839566,0.0008521734,0.0009320393,0.001026043,0.000587863],"domain_scores_gemma":[0.9950718,0.0008640125,0.0003712238,0.003307771,0.0002274897,0.0001576628],"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":[0.0005550498,0.00457261,0.001441221,0.00003073903,0.0007687514,0.000669278,0.009310486,0.08502603,0.02136265,0.3861506,0.0149623,0.4751503],"study_design_scores_gemma":[0.0009422363,0.0001028246,0.0005517791,0.0001729773,0.00001761411,0.0001712117,0.001385608,0.9834186,0.00008035779,0.006272886,0.006205232,0.000678672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3265319,0.002509258,0.4931214,0.1000916,0.0101181,0.002102287,0.0004081629,0.001358016,0.06375933],"genre_scores_gemma":[0.9891139,0.0008662965,0.005097037,0.001792441,0.00005170767,0.0004672261,0.0002648756,0.00004319403,0.002303366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8983926,"threshold_uncertainty_score":0.9997459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07471750352792537,"score_gpt":0.3028058148431328,"score_spread":0.2280883113152075,"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."}}