{"id":"W4214926007","doi":"10.1145/3510449","title":"Binary Fuse Filters: Fast and Smaller Than Xor Filters","year":2022,"lang":"en","type":"article","venue":"ACM Journal of Experimental Algorithmics","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"","keywords":"Bloom filter; Cuckoo; Binary number; Fuse (electrical); Computer science; Cuckoo search; Algorithm; Upper and lower bounds; Quotient; Mathematics; Arithmetic; Engineering; Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0002924336,0.0001597149,0.000211006,0.0001772344,0.0002948604,0.0001457184,0.001246993,0.00002682322,0.00004296052],"category_scores_gemma":[0.00001860809,0.0001504745,0.0001450901,0.0001674267,0.00005402106,0.000557726,0.001389409,0.0003486916,0.000003588427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001271942,"about_ca_system_score_gemma":0.00005592462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003779885,"about_ca_topic_score_gemma":4.562863e-7,"domain_scores_codex":[0.9986476,0.0001056665,0.0003332369,0.0002253094,0.0004526123,0.000235632],"domain_scores_gemma":[0.9990984,0.00007712545,0.0002334741,0.0003873536,0.00004967219,0.0001539584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007491292,0.003307314,0.005507483,0.00003223542,0.0009431161,0.004416508,0.03135002,0.002585856,0.7742088,0.002949047,0.0439924,0.1299581],"study_design_scores_gemma":[0.02874143,0.03447235,0.01479359,0.0005572205,0.0003031337,0.04044627,0.1059992,0.5503569,0.1603679,0.004713289,0.05304424,0.006204467],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865098,0.003517743,0.006700801,0.001368675,0.001630057,0.00008626995,0.00001365377,0.00003727627,0.000135696],"genre_scores_gemma":[0.9804183,0.000103596,0.0183581,0.0007579997,0.0001741588,0.000006755852,0.000002657403,0.00001472906,0.0001636597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6138408,"threshold_uncertainty_score":0.6136171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087264857275021,"score_gpt":0.2426543320571644,"score_spread":0.2217816834844142,"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."}}