{"id":"W2145186067","doi":"10.1109/icde.2004.1319984","title":"A succinct physical storage scheme for efficient evaluation of path queries in XML","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Computer science; XML; Path (computing); Scheme (mathematics); Node (physics); Matching (statistics); Pattern matching; XML Signature; Streaming XML; XML database; Efficient XML Interchange; Path expression; Theoretical computer science; Computer network; Programming language; World Wide Web; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003036315,0.0007604467,0.001046034,0.001383501,0.001155433,0.003270087,0.002980806,0.0009165098,0.006944782],"category_scores_gemma":[0.01048568,0.0008957952,0.0004476017,0.002739616,0.001392672,0.009303127,0.004322295,0.001164833,0.002583386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324345,"about_ca_system_score_gemma":0.002034107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001422192,"about_ca_topic_score_gemma":0.001694017,"domain_scores_codex":[0.9972868,0.0004944619,0.0005548192,0.0003303128,0.001179147,0.0001544804],"domain_scores_gemma":[0.9923961,0.00161244,0.0006682227,0.004005476,0.001109604,0.0002082907],"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":[0.002078274,0.000404488,0.004335567,0.0009694136,0.0001195505,0.0005535581,0.001021486,0.04046097,0.09574604,0.1446279,0.03174363,0.6779391],"study_design_scores_gemma":[0.0005396944,0.001070415,0.002335589,0.00019967,0.0001671495,0.002400086,0.0005056252,0.6764875,0.1435148,0.08481657,0.08758548,0.0003774051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01756813,0.0003789528,0.9725552,0.000299658,0.0001015814,0.0003295515,0.0006584086,0.006519426,0.001589101],"genre_scores_gemma":[0.2557273,0.0004847427,0.7353608,0.0002684428,0.000129539,0.0005350947,0.002294761,0.0006401219,0.004559159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006944782,"threshold_uncertainty_score":0.02323258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695081419634111,"score_gpt":0.3079136312393318,"score_spread":0.2809628170429907,"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."}}