{"id":"W2027088687","doi":"10.5539/cis.v2n1p115","title":"A Study On Query Optimization for Federated Database Systems","year":2009,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Query optimization; Database; Information retrieval; View; Sargable; Web search query; Database design; Search engine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0007170546,0.00008665089,0.00008387733,0.0002978461,0.0004364789,0.002291706,0.0005692717,0.00001190755,5.230121e-7],"category_scores_gemma":[0.00002353908,0.00007165518,0.00001097284,0.0006511058,0.00003599049,0.01545371,0.0001725409,0.00003550764,0.00001112489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001996475,"about_ca_system_score_gemma":0.00003823929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002314635,"about_ca_topic_score_gemma":5.924213e-8,"domain_scores_codex":[0.999055,0.00001464851,0.0002237663,0.0002126844,0.000323157,0.0001707407],"domain_scores_gemma":[0.999348,0.00002684508,0.00008797206,0.0002918696,0.0001757572,0.00006952055],"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":[0.0000261944,0.0003757207,0.0001358266,0.00004803968,0.00001350783,0.000004214771,0.004090576,0.09712031,0.00003780551,0.3072665,0.009310615,0.5815707],"study_design_scores_gemma":[0.000417218,0.0003986206,0.0016758,0.00001381317,0.000001613061,0.000002956936,0.0001013685,0.9953776,0.00002700696,0.00003208976,0.001850763,0.000101144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002914931,0.000005096847,0.9946119,0.0002473232,0.0004881851,0.0005643666,0.000006156431,0.0001113709,0.001050732],"genre_scores_gemma":[0.8393218,0.00001404213,0.1578028,0.002618023,0.0001073991,0.00003311499,0.00006750915,0.000002380405,0.00003296811],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8982573,"threshold_uncertainty_score":0.998744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732586993840915,"score_gpt":0.276357045068118,"score_spread":0.2490311751297088,"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."}}