{"id":"W58025431","doi":"","title":"DB2 LUW optimizer: beginner to intermediate guide","year":2011,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Section (typography); SQL; Compiler; Programming language; Database; Heuristic; Information retrieval; Artificial intelligence; Operating system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001994717,0.002283293,0.00154467,0.001332516,0.0009160392,0.005447802,0.003722145,0.001634686,0.3657857],"category_scores_gemma":[0.008373839,0.001663128,0.00134011,0.00117671,0.0004574685,0.004688429,0.004435403,0.004257735,0.3531477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181432,"about_ca_system_score_gemma":0.001533918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001633897,"about_ca_topic_score_gemma":0.002072687,"domain_scores_codex":[0.9981687,0.0002009478,0.0001032639,0.0003922571,0.0008935727,0.0002411456],"domain_scores_gemma":[0.9966857,0.0007135735,0.00008829647,0.0003993066,0.001497068,0.0006161057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001727355,0.0001204042,0.0001650283,0.0002617274,0.000009166058,0.0001961143,0.0003691787,0.0007040515,0.004091306,0.005770726,0.8776198,0.1105197],"study_design_scores_gemma":[0.00004208058,0.00004983258,0.0003809321,0.0001331799,0.000005392255,0.0002505406,0.0001972929,0.002419025,0.002287191,0.004041689,0.9901513,0.00004164522],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004177584,0.001753942,0.4670452,0.006245274,0.002720501,0.00150185,0.01505921,0.1624992,0.3389972],"genre_scores_gemma":[0.01930462,0.002220104,0.3143731,0.007471881,0.00114267,0.001686846,0.0226139,0.1230779,0.508109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3657857,"threshold_uncertainty_score":0.9046297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.515187988773632,"score_gpt":0.52639787944863,"score_spread":0.011209890674998,"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."}}