{"id":"W1510826524","doi":"10.1007/978-3-642-00887-0_55","title":"Materialized View Selection in XML Databases","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materialized view; Computer science; XML; Selection (genetic algorithm); XML database; Information retrieval; Data warehouse; Database; Relational database management system; Context (archaeology); Graph; Streaming XML; XML validation; Efficient XML Interchange; Relational database; Theoretical computer science; View; World Wide Web; Database design; Artificial intelligence","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":[0.002274492,0.0005858819,0.001010486,0.001410517,0.0007258938,0.003589427,0.002323041,0.0008948517,0.01106545],"category_scores_gemma":[0.004057553,0.0008405878,0.0008806759,0.002547819,0.0009797311,0.005200744,0.002157351,0.001375151,0.002826703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008376469,"about_ca_system_score_gemma":0.0006281404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101314,"about_ca_topic_score_gemma":0.001412885,"domain_scores_codex":[0.9978499,0.000582424,0.0002180664,0.0002503928,0.000957107,0.0001420969],"domain_scores_gemma":[0.9981914,0.0008942081,0.00006307339,0.0005559441,0.000223812,0.00007152095],"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":[0.0007128295,0.0002531249,0.001618812,0.0007233523,0.00009029602,0.0006552874,0.0007300857,0.01707896,0.01567682,0.217502,0.03092567,0.7140329],"study_design_scores_gemma":[0.0002053203,0.0003266747,0.001540095,0.0004500172,0.0001953452,0.001503675,0.000716384,0.322703,0.07337967,0.4173998,0.1814205,0.0001595907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.023544,0.002778407,0.9480128,0.0004026247,0.0001455829,0.0001601379,0.0007212929,0.00810106,0.01613413],"genre_scores_gemma":[0.2300572,0.002359192,0.7325315,0.0003212821,0.0001920588,0.0001954686,0.003925699,0.002007661,0.02840978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01106545,"threshold_uncertainty_score":0.03701764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02280143752678639,"score_gpt":0.2710076934982822,"score_spread":0.2482062559714958,"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."}}