{"id":"W1508620658","doi":"","title":"Supporting capacity planning for DB2 UDB","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Capacity planning; Computer science; IBM; Workload; Capacity management; Online transaction processing; Process (computing); Database; Distributed computing; Transaction processing; Operating system; Database transaction","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":[0.003093448,0.0006491461,0.0006581882,0.0007413508,0.001418586,0.003316453,0.002321938,0.001167284,0.007698907],"category_scores_gemma":[0.01432019,0.0006332033,0.0003879864,0.001628753,0.0006337116,0.002757782,0.001628582,0.001027267,0.001289034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0020913,"about_ca_system_score_gemma":0.003501878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0289181,"about_ca_topic_score_gemma":0.01956986,"domain_scores_codex":[0.9974139,0.001076256,0.0001087286,0.0002615459,0.00064727,0.0004923588],"domain_scores_gemma":[0.9940673,0.003025549,0.0003962601,0.0009320197,0.001110522,0.0004683291],"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":[0.0002498291,0.0001976377,0.004253138,0.00015751,0.00003332679,0.0003717136,0.0004550536,0.800263,0.005862011,0.07959428,0.02776579,0.08079667],"study_design_scores_gemma":[0.00001088243,0.00001265306,0.0001653786,0.000008908798,0.000002957302,0.00003136262,0.00007523946,0.9853176,0.001131196,0.00771437,0.005519645,0.000009731153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1507132,0.0006081676,0.7859722,0.002825371,0.0001653764,0.0003469911,0.001712777,0.01197836,0.04567763],"genre_scores_gemma":[0.8854377,0.0002066635,0.1090934,0.0002101509,0.00004484997,0.0001587009,0.0008823615,0.0003946716,0.003571425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0289181,"threshold_uncertainty_score":0.05749959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0730831974408855,"score_gpt":0.3065056263743842,"score_spread":0.2334224289334987,"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."}}