{"id":"W7132955618","doi":"","title":"Robust Fronthaul in Wireless Networks: A Caching and Traffic Prediction Approach","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Latency (audio); Wireless network; Wireless; Cloud computing; Markov decision process; Telecommunications link; Radio access network; Markov process; Process (computing)","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009285594,0.0007080167,0.0007428132,0.0006122161,0.0003356329,0.001099341,0.0006775235,0.0006470416,0.00000819465],"category_scores_gemma":[0.00003035212,0.0007591232,0.0002176317,0.0009073727,0.00007394544,0.0005465448,0.0002130207,0.001974613,0.00001900647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002598623,"about_ca_system_score_gemma":0.0002394789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001906859,"about_ca_topic_score_gemma":0.001088584,"domain_scores_codex":[0.9959328,0.0003162003,0.0006866307,0.001752819,0.0005737566,0.000737767],"domain_scores_gemma":[0.9986428,0.0001446145,0.0002620629,0.0006378351,0.00008952666,0.0002231493],"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":[0.0001733224,0.0002912859,0.0003910561,0.0009611454,0.000169471,0.0001523883,0.06511732,0.8553155,0.0001906188,0.00121875,0.000898331,0.07512079],"study_design_scores_gemma":[0.0005689408,0.0001242912,0.00150364,0.001628441,0.000146912,0.00006748781,0.01182161,0.9834019,0.00000431993,0.00002144742,0.00009242135,0.0006185802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8407773,0.0134238,0.1384962,0.0001972205,0.003906985,0.0007008451,0.000007562794,0.0003371335,0.002152978],"genre_scores_gemma":[0.9901229,0.001257236,0.0005551084,0.00005533377,0.0004972494,0.00009303641,0.0002651252,0.00007759952,0.007076442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1493455,"threshold_uncertainty_score":0.9999376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571057202059684,"score_gpt":0.2561260744045028,"score_spread":0.230415502383906,"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."}}