{"id":"W2159157420","doi":"10.14778/1454159.1454222","title":"Scheduling continuous queries in data stream management systems","year":2008,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Salient; Scheduling (production processes); Distributed computing; Operations research; Mathematical optimization; Artificial intelligence","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":[0.005133814,0.0004865259,0.001142402,0.0006229812,0.0008626275,0.00270202,0.001632305,0.0009451196,0.001066366],"category_scores_gemma":[0.008772746,0.0004761955,0.0003814251,0.001686486,0.000987894,0.002143745,0.001260465,0.001284303,0.0002330888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407049,"about_ca_system_score_gemma":0.00170174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004474153,"about_ca_topic_score_gemma":0.003050505,"domain_scores_codex":[0.9974962,0.0009128967,0.0002609561,0.0003519499,0.0007478809,0.0002300706],"domain_scores_gemma":[0.9962631,0.002236809,0.0002226255,0.0003584161,0.0004713206,0.0004476533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002467768,0.000629263,0.008611782,0.0009739257,0.0002058316,0.0007326429,0.001780196,0.5425757,0.03815749,0.151466,0.02177869,0.2306207],"study_design_scores_gemma":[0.0001130462,0.0001157337,0.000594024,0.00001880353,0.00002283124,0.00005956006,0.0001631889,0.9676853,0.003192659,0.02173685,0.006276425,0.00002140495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1251914,0.005833382,0.8604769,0.001910274,0.0003712638,0.0003123994,0.0003890796,0.002187522,0.003327765],"genre_scores_gemma":[0.8263469,0.002114477,0.1684951,0.0003208312,0.0003883163,0.0001957367,0.0003881988,0.0001417529,0.00160852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005133814,"threshold_uncertainty_score":0.02715051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159481624336894,"score_gpt":0.2433917383999664,"score_spread":0.2117969221565975,"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."}}