{"id":"W2488719221","doi":"10.4018/978-1-60566-242-8.ch070","title":"On the Query Evaluation in XML Databases","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Joins; Computer science; Twig; XML; XML database; XPath; Matching (statistics); Query optimization; Query language; Database; Theoretical computer science; Information retrieval; Data mining; Mathematics; Programming language; World Wide Web","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":[0.005307941,0.001450475,0.002174922,0.001634481,0.0009863211,0.005543336,0.002988937,0.001604808,0.008606767],"category_scores_gemma":[0.01227746,0.0006533848,0.0009426455,0.005360092,0.0018844,0.00870563,0.00291276,0.002433058,0.002646129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002048119,"about_ca_system_score_gemma":0.001205013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003863426,"about_ca_topic_score_gemma":0.002361606,"domain_scores_codex":[0.9925879,0.002955387,0.0005463065,0.0007162129,0.002867625,0.0003266603],"domain_scores_gemma":[0.9943398,0.004233838,0.0001074722,0.000647172,0.0005633103,0.0001084821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005250241,0.0001687184,0.0009948956,0.001152433,0.00008563716,0.0004295308,0.0006723668,0.03418178,0.003824628,0.2307642,0.06011022,0.6670906],"study_design_scores_gemma":[0.0001342542,0.0001525353,0.0007764191,0.0004787162,0.0001007197,0.001010301,0.0005206718,0.5657597,0.007495502,0.2961133,0.127402,0.0000558663],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01279057,0.02433847,0.9249325,0.003391524,0.000446002,0.0003799484,0.0005986487,0.002211126,0.03091117],"genre_scores_gemma":[0.1683384,0.02066743,0.7658527,0.001722061,0.001086324,0.0006226756,0.002219526,0.001157956,0.03833304],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008606767,"threshold_uncertainty_score":0.0287925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04637975800712896,"score_gpt":0.2910003106542999,"score_spread":0.244620552647171,"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."}}