{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003690921,0.00009930158,0.0001650219,0.0003205444,0.00006285049,0.00007125724,0.0007083385,0.00005257667,0.00001979103],"category_scores_gemma":[0.0000264465,0.00007874927,0.00002674283,0.0009637792,0.00002558947,0.002072624,0.0005679373,0.0001180952,0.000003660705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001704571,"about_ca_system_score_gemma":0.00003946317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005210668,"about_ca_topic_score_gemma":0.005035994,"domain_scores_codex":[0.9989617,0.00003024858,0.0002508012,0.0004294168,0.0001599697,0.0001678946],"domain_scores_gemma":[0.9984071,0.00003650729,0.0000931333,0.001366336,0.00005510285,0.00004186577],"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":[0.000005884925,0.000257395,0.02852373,0.0000683044,0.0001011231,0.00007705773,0.0006482885,0.00009700218,0.08433517,0.4076146,0.0002966015,0.4779748],"study_design_scores_gemma":[0.0001708068,0.00003402771,0.002454464,0.00004219347,0.00005593684,0.00002710019,0.00004781565,0.8746297,0.07544337,0.00185055,0.04476026,0.0004838001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01646953,0.00001115997,0.9813756,0.00008587901,0.00006947883,0.0001478926,0.00002233897,0.0001580356,0.001660041],"genre_scores_gemma":[0.1774562,0.000003407642,0.8223113,0.00002566353,0.00003641378,0.000008121846,0.00004980832,0.000004155642,0.0001049358],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8745327,"threshold_uncertainty_score":0.3211302,"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."}}