{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001577414,0.001379378,0.001415546,0.0008268125,0.0005336384,0.00169347,0.002385895,0.001576743,0.001577573],"category_scores_gemma":[0.0041862,0.0008065104,0.0009025971,0.001303267,0.000998626,0.001884011,0.001271647,0.00199375,0.0002904523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762023,"about_ca_system_score_gemma":0.001714537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01569542,"about_ca_topic_score_gemma":0.008337308,"domain_scores_codex":[0.9992509,0.0002616388,0.00003469569,0.0001484708,0.0001715861,0.0001327489],"domain_scores_gemma":[0.9972655,0.001956023,0.0002350953,0.000113426,0.0003382129,0.00009171315],"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":[0.00002089024,0.00002733163,0.0002994257,0.00003439989,0.00002406755,0.00003731685,0.00002046326,0.9797248,0.0003313326,0.01019212,0.000420515,0.008867363],"study_design_scores_gemma":[0.000001136296,0.000005309038,0.00002468226,0.000003079314,0.000003267623,0.000002940548,0.000002482263,0.9977957,0.00004378573,0.002032855,0.00008252143,0.000002265963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01490807,0.001673089,0.9795074,0.0007187294,0.00009894827,0.00004847007,0.0001049831,0.0001840451,0.002756249],"genre_scores_gemma":[0.8557468,0.004097153,0.1314086,0.0003657802,0.0005853781,0.0002387577,0.0003258592,0.0001344282,0.007097252],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01569542,"threshold_uncertainty_score":0.03120816,"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."}}