{"id":"W4385270603","doi":"10.1109/icde55515.2023.00076","title":"SASPAR: Shared Adaptive Stream Partitioning","year":2023,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Stream processing; Partition (number theory); Heuristics; Latency (audio); Distributed computing; Data stream; Query plan; Bandwidth (computing); Throughput; Parallel computing; Computer network; Search engine; Operating system; Sargable","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":[0.000992503,0.00121457,0.0007674097,0.0005988083,0.0007176535,0.001207417,0.002708911,0.0005524682,0.002228107],"category_scores_gemma":[0.003186633,0.0004133413,0.0005910013,0.001035487,0.0006381767,0.002235071,0.002209975,0.001086289,0.0006999383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009298973,"about_ca_system_score_gemma":0.001801524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003945774,"about_ca_topic_score_gemma":0.006011155,"domain_scores_codex":[0.9988608,0.0001739426,0.00009294711,0.0003123508,0.0003912357,0.0001685626],"domain_scores_gemma":[0.998412,0.0004089691,0.0001199006,0.000600544,0.0003260036,0.0001326392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001977502,0.0007199792,0.009874707,0.0003789497,0.00031538,0.0005393434,0.0004329268,0.3355809,0.1439714,0.01618663,0.03387592,0.4561463],"study_design_scores_gemma":[0.0001049097,0.000216525,0.001108426,0.000007052917,0.00003292661,0.000171831,0.0000740279,0.9543958,0.03176535,0.005189125,0.00690191,0.00003213573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1132717,0.0005969019,0.8521235,0.000308872,0.0001617092,0.0003988689,0.0007295496,0.0269932,0.005415749],"genre_scores_gemma":[0.6475404,0.0002552854,0.3456365,0.0002137208,0.00007027146,0.0002955496,0.001952984,0.001143516,0.002891776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003945774,"threshold_uncertainty_score":0.007845581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04336431057814042,"score_gpt":0.2404583809533032,"score_spread":0.1970940703751628,"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."}}