{"id":"W2025036269","doi":"10.1145/1923947.1923969","title":"Lightweight problem determination in DBMSs using data stream analysis techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); Queen's University","funders":"","keywords":"Computer science; Overhead (engineering); IBM; Task (project management); Set (abstract data type); Database; Data mining; Data stream; Stream processing; Real-time computing; Distributed computing; Operating system; Programming language","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":[0.004630375,0.00189778,0.002184309,0.002896472,0.001910672,0.005135807,0.002929143,0.001402074,0.002232739],"category_scores_gemma":[0.02374493,0.001446773,0.001774398,0.003461852,0.001203899,0.007188079,0.003806987,0.002609264,0.001237165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238436,"about_ca_system_score_gemma":0.003104629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004239181,"about_ca_topic_score_gemma":0.007574004,"domain_scores_codex":[0.991313,0.002299785,0.0009441153,0.00152767,0.003409488,0.0005060319],"domain_scores_gemma":[0.9785516,0.0125412,0.00206067,0.003883239,0.002348138,0.0006151667],"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":[0.001136171,0.001251284,0.02207608,0.001361555,0.0004854555,0.0008012312,0.002403022,0.096347,0.03904882,0.01668109,0.01786374,0.8005447],"study_design_scores_gemma":[0.0002081316,0.000230776,0.002908921,0.00008344327,0.0001001675,0.0004212902,0.0009842025,0.9192585,0.02753443,0.03999045,0.008202173,0.0000774576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0829638,0.0008298801,0.8896953,0.000893182,0.00007891341,0.0005683112,0.0007198014,0.02216959,0.00208121],"genre_scores_gemma":[0.2099423,0.0003223504,0.7855686,0.000226863,0.00006766497,0.0002540321,0.001290864,0.000752074,0.001575266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005135807,"threshold_uncertainty_score":0.02448803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02889349043808061,"score_gpt":0.3127612501953509,"score_spread":0.2838677597572703,"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."}}