{"id":"W4411552971","doi":"10.1145/3736548.3737836","title":"PaperCache: In-Memory Caching with Dynamic Eviction Policies","year":2025,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Eviction; Computer science; Computer network; Computer security; Political science","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":[0.001113214,0.001071835,0.0007877988,0.0009657412,0.0007018436,0.001763733,0.003369194,0.001083098,0.002207714],"category_scores_gemma":[0.005781669,0.0005368605,0.0003489,0.001968739,0.0005858188,0.00273095,0.00109971,0.001083195,0.0006416898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263889,"about_ca_system_score_gemma":0.002294519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008348243,"about_ca_topic_score_gemma":0.01058219,"domain_scores_codex":[0.998477,0.000277038,0.0001901423,0.0002235276,0.0005502102,0.0002820011],"domain_scores_gemma":[0.9937096,0.001038892,0.0004808265,0.002968959,0.001467146,0.0003346478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006647997,0.002558456,0.04335516,0.00145546,0.0008651455,0.0009729018,0.001011296,0.1783195,0.1380777,0.02356498,0.08439512,0.5187764],"study_design_scores_gemma":[0.0005659786,0.001522778,0.006555978,0.000119155,0.000333921,0.0009146205,0.0001860457,0.7448819,0.171927,0.008054227,0.06471431,0.0002241645],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5720244,0.005598076,0.3122368,0.0008713869,0.0008709918,0.0008954325,0.002780175,0.08552761,0.01919513],"genre_scores_gemma":[0.8993356,0.0008440985,0.08789075,0.0004673687,0.00009849799,0.0002335958,0.001987002,0.001282666,0.007860506],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008348243,"threshold_uncertainty_score":0.01659936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005029596589708506,"score_gpt":0.2263338951616403,"score_spread":0.2213042985719318,"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."}}