{"id":"W2029487844","doi":"10.1007/s00778-010-0184-8","title":"Efficient evaluation of generalized tree-pattern queries on XML streams","year":2010,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"XPath; Computer science; XML; Scalability; Query language; Fragment (logic); Spatial query; Theoretical computer science; Query optimization; Tree (set theory); Focus (optics); Node (physics); Time complexity; Data mining; XML database; Information retrieval; Algorithm; Web query classification; Web search query; Database; Search engine; Mathematics","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":[0.001754644,0.0001036256,0.0001391405,0.00007028648,0.0002232758,0.00005708827,0.0004289837,0.00002947545,0.00006988321],"category_scores_gemma":[0.00008384162,0.00005876017,0.00006969023,0.000137278,0.00008119456,0.0001414471,0.0000875013,0.0002658508,0.00001748916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002457119,"about_ca_system_score_gemma":0.0001089864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004180247,"about_ca_topic_score_gemma":0.00008499122,"domain_scores_codex":[0.9984888,0.0002133593,0.0002814029,0.0001364813,0.0007103971,0.0001695361],"domain_scores_gemma":[0.9988312,0.00007041719,0.0002675796,0.0005264878,0.000242776,0.00006157554],"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":[0.00004281127,0.0001539894,0.0004341483,0.00001191281,0.000055035,0.00001026555,0.00285513,0.02252266,0.04590446,0.1124628,0.0008893724,0.8146574],"study_design_scores_gemma":[0.003791369,0.0005882238,0.01434719,0.0002385891,0.0001027204,0.0009173322,0.0006385213,0.8579583,0.08624307,0.01074967,0.02380548,0.0006195608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7358871,0.0000956433,0.2617732,0.0006016794,0.001064731,0.0001084412,0.000007161098,0.00001836538,0.000443733],"genre_scores_gemma":[0.990925,0.00001090181,0.00860931,0.00009162608,0.0002873937,0.000006986631,0.000001547881,0.00000668414,0.00006058277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8354356,"threshold_uncertainty_score":0.239617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02671680487953133,"score_gpt":0.2935799402125482,"score_spread":0.2668631353330169,"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."}}