{"id":"W2081869611","doi":"10.5555/1070432.1070548","title":"An optimal Bloom filter replacement","year":2005,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":153,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bloom filter; Hash function; Data structure; Set (abstract data type); Computer science; Element (criminal law); Representation (politics); Amortized analysis; Filter (signal processing); Algorithm; Theoretical computer science; Function (biology); Perfect hash function; Constant (computer programming); Bloom; Hash table","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":[0.001768647,0.0005317471,0.001867851,0.001332848,0.001308259,0.001904687,0.00266751,0.001707671,0.006359504],"category_scores_gemma":[0.009030839,0.0005678842,0.0008486381,0.002339755,0.0009159445,0.00551276,0.002124021,0.000928383,0.001949231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002121991,"about_ca_system_score_gemma":0.003265819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00230383,"about_ca_topic_score_gemma":0.002465424,"domain_scores_codex":[0.9975826,0.0005144984,0.0001942672,0.0004757983,0.0008811231,0.0003516971],"domain_scores_gemma":[0.9964348,0.0009133545,0.0001973874,0.001763207,0.0005334082,0.0001577904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001701208,0.0005419982,0.004577326,0.0004187148,0.0001250543,0.0003478701,0.000587506,0.05827909,0.02765386,0.209156,0.03307498,0.6635363],"study_design_scores_gemma":[0.0004346255,0.0005836484,0.001035868,0.0001598012,0.0001477173,0.00150692,0.0003430552,0.7292411,0.02983285,0.1588823,0.0777438,0.00008838976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07107142,0.00180072,0.9075099,0.00172339,0.0003736129,0.0003150904,0.0008269556,0.002690357,0.01368864],"genre_scores_gemma":[0.304873,0.0008154564,0.6775182,0.0007263798,0.000213965,0.0003324379,0.000981561,0.0002841405,0.01425486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006359504,"threshold_uncertainty_score":0.02127469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162427078857109,"score_gpt":0.2517560130831717,"score_spread":0.2401317422946007,"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."}}