{"id":"W3206697535","doi":"10.1145/3471904","title":"Worst-Case Execution Time Calculation for Query-Based Monitors by Witness Generation","year":2021,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Real-Time Systems Scheduling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Witness; Query optimization; Database; Programming language","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":[0.0002607218,0.0001496744,0.0001563406,0.0001131822,0.0002699212,0.0001436769,0.0002502749,0.0001191425,0.000009107032],"category_scores_gemma":[0.00004444957,0.0001820558,0.0001049253,0.0007037606,0.00003279036,0.0008720327,0.00006359127,0.0000746668,0.00005197915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001994881,"about_ca_system_score_gemma":0.0001468298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001138717,"about_ca_topic_score_gemma":0.00002538771,"domain_scores_codex":[0.9987469,0.000142898,0.0001775895,0.0006108436,0.00008594133,0.0002358546],"domain_scores_gemma":[0.9988657,0.00009738373,0.0001401262,0.0004967973,0.0002872003,0.0001127436],"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":[0.00004921789,0.0002383295,0.001815504,0.00008040857,0.00008555827,0.001570423,0.0002911048,0.7147615,0.1130906,0.1642583,0.001931297,0.001827725],"study_design_scores_gemma":[0.0005878385,0.00003272663,0.00005795406,0.00001953474,0.00002440307,0.00004715591,0.00004192943,0.9703763,0.02735753,0.001096966,0.0001471546,0.0002105409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3789421,0.00001732411,0.6204069,0.00006252597,0.0001971682,0.0001626349,0.000004935247,0.00009708272,0.0001093597],"genre_scores_gemma":[0.9904904,0.00000178761,0.008213603,0.00004525998,0.0001094964,0.000002464502,0.00007479505,0.000012978,0.001049241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6121933,"threshold_uncertainty_score":0.7424021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05359104345350239,"score_gpt":0.1897402398853804,"score_spread":0.136149196431878,"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."}}