{"id":"W1586507268","doi":"10.1007/978-3-642-12450-1_10","title":"Parameterized Analysis of Paging and List Update Algorithms","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Parameterized complexity; Locality; Cache; Locality of reference; Algorithm; Online algorithm; Set (abstract data type); Cache algorithms; Working set; Memory hierarchy; CPU cache; Theoretical computer science; Parallel 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":[0.005112497,0.002181586,0.002685541,0.002709343,0.001893543,0.007625809,0.007190526,0.002848845,0.02201452],"category_scores_gemma":[0.04667685,0.001831619,0.002448057,0.005827427,0.002644392,0.01397981,0.003592102,0.005427893,0.002845544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006875718,"about_ca_system_score_gemma":0.004903798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004756529,"about_ca_topic_score_gemma":0.004104688,"domain_scores_codex":[0.9930862,0.002347113,0.000298297,0.0008439444,0.002151806,0.001272694],"domain_scores_gemma":[0.9649662,0.02387782,0.001873993,0.005883382,0.002425866,0.0009727844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006404231,0.0003440301,0.002146794,0.0003803414,0.0001471996,0.000118868,0.0003294152,0.3488998,0.002992841,0.5374619,0.02242359,0.08411489],"study_design_scores_gemma":[0.00004333493,0.00003887475,0.0004433899,0.00003526359,0.00006128375,0.00006409015,0.00004403856,0.7520713,0.0009467147,0.2434488,0.002777376,0.00002557558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05492837,0.002841619,0.9038395,0.002438106,0.000261826,0.0002518129,0.001061885,0.00233579,0.03204125],"genre_scores_gemma":[0.7057191,0.002919869,0.2499729,0.0007407158,0.001227229,0.0008025451,0.002937212,0.002825219,0.03285517],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02201452,"threshold_uncertainty_score":0.07364595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174757848577018,"score_gpt":0.2632109931213892,"score_spread":0.2457352082636874,"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."}}