{"id":"W4402043624","doi":"10.14778/3681954.3682027","title":"Aleph Filter: To Infinity in Constant Time","year":2024,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Infinity; Constant (computer programming); Aleph; Mathematics; Filter (signal processing); Mathematical analysis; Physics; Computer science; Programming language; Particle physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003556118,0.0001027788,0.0001327531,0.0001342969,0.00003912211,0.0001504841,0.0007723571,0.0000252503,0.00001294438],"category_scores_gemma":[0.00005401309,0.00007144994,0.00008157912,0.0004560739,0.00002645026,0.0002163324,0.0005476628,0.000137719,0.00008407002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008121876,"about_ca_system_score_gemma":0.00003761272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009748161,"about_ca_topic_score_gemma":0.000003547663,"domain_scores_codex":[0.9990473,0.000006099103,0.0002140626,0.000265453,0.0002698074,0.0001972798],"domain_scores_gemma":[0.9996616,0.00004612881,0.00003993532,0.0001422286,0.00005536609,0.00005479914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005501973,0.0003049544,0.005806114,0.0003442544,0.00009202189,0.00002816599,0.007475081,0.0001360361,0.5270669,0.3577624,0.05010116,0.05082787],"study_design_scores_gemma":[0.003036953,0.001435022,0.009764128,0.006825929,0.0001323149,0.0003951469,0.00100124,0.2136794,0.5288795,0.07759264,0.1548627,0.002394976],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337267,0.0005501734,0.0009986492,0.009900881,0.0008740588,0.0006585718,0.00001312075,0.0002889424,0.05298889],"genre_scores_gemma":[0.9975607,0.00001329743,0.0007237637,0.0004451276,0.00003036551,0.00002630795,1.624863e-7,0.000005746174,0.001194571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2801698,"threshold_uncertainty_score":0.2913644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01054755328993164,"score_gpt":0.2108183152649619,"score_spread":0.2002707619750302,"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."}}