{"id":"W2133491514","doi":"10.1145/872757.872832","title":"A comprehensive XQuery to SQL translation using dynamic interval encoding","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"XQuery; Computer science; SQL; Query language; XML; Information retrieval; Relational database; Programming language; Database; Theoretical computer science; XML database; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009530562,0.000104382,0.0001332266,0.00008710795,0.00009969575,0.00004313954,0.0001384881,0.0000249098,0.00001770879],"category_scores_gemma":[0.00001604261,0.00009386462,0.00004149731,0.0002636151,0.00001472739,0.0006902412,0.00005136345,0.0000560968,0.00002888526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004759066,"about_ca_system_score_gemma":0.00003236202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004807599,"about_ca_topic_score_gemma":0.000045666,"domain_scores_codex":[0.9991589,0.00006058631,0.0001907202,0.0002695165,0.0001284764,0.0001918275],"domain_scores_gemma":[0.9994873,0.00005234301,0.00003808175,0.0002928055,0.00005637711,0.0000730449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001496077,0.00005927843,0.0002536694,0.00009889247,0.00003582647,0.00004954312,0.004445492,0.01013773,0.2175958,0.7032709,0.0001706543,0.06386718],"study_design_scores_gemma":[0.0009471041,0.0002188634,0.0006319106,0.0003234993,0.0000136328,0.0003216454,0.001816806,0.6746038,0.02700039,0.00269466,0.2902812,0.001146471],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03579478,0.00009877958,0.9611993,0.00009429924,0.0003443653,0.0001505747,0.000003500398,0.0001075791,0.002206867],"genre_scores_gemma":[0.4527376,0.000002404112,0.5469229,0.0002283095,0.00001055163,0.00000404701,0.000001665438,0.000005330606,0.00008718658],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7005762,"threshold_uncertainty_score":0.3827688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05424338726814418,"score_gpt":0.3097391134711411,"score_spread":0.255495726202997,"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."}}