{"id":"W4416649891","doi":"10.1109/tnse.2025.3637123","title":"Intelligent Edge Caching Strategies for Optimized Content Delivery","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cache; Enhanced Data Rates for GSM Evolution; Wireless; Content delivery; Volume (thermodynamics); Edge computing; Mobile device; Wireless network; Edge device; Graph","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001511555,0.0004274506,0.0004347507,0.0005863876,0.001545182,0.001448434,0.000927409,0.0001327181,0.000004231404],"category_scores_gemma":[0.00002550535,0.0004398359,0.0002242744,0.001669191,0.0003002127,0.001397887,0.00002169631,0.0005443657,0.000004250851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002881523,"about_ca_system_score_gemma":0.0009608433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001476358,"about_ca_topic_score_gemma":0.00002216179,"domain_scores_codex":[0.9969544,0.00003664452,0.0005467988,0.0009653113,0.0004773102,0.001019495],"domain_scores_gemma":[0.9982919,0.000425953,0.0000826028,0.0005469098,0.0003918923,0.0002607138],"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":[0.00007198345,0.00006317287,0.000001551246,0.00008161002,0.00007377256,0.000003887372,0.0003570239,0.904466,0.003968489,0.005652979,0.000142089,0.08511747],"study_design_scores_gemma":[0.0006667543,0.0001954705,0.00002537503,0.0006958438,0.00009288253,0.00001127188,0.0004061435,0.9944615,0.001974749,0.0001280511,0.0009140209,0.0004278921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02159424,0.002010063,0.9674444,0.0004574253,0.00747362,0.000583007,0.000009926145,0.0002038167,0.0002235094],"genre_scores_gemma":[0.9899508,0.001204383,0.007732321,0.0004566528,0.0001521952,0.0001000314,4.879005e-7,0.00001816606,0.0003849569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9683565,"threshold_uncertainty_score":0.9998053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02930854887855782,"score_gpt":0.2357852844012445,"score_spread":0.2064767355226866,"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."}}