{"id":"W2167866332","doi":"","title":"HePToX: marrying XML and heterogeneity in your P2P databases","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Schema (genetic algorithms); XML; XML database; Information retrieval; Database; XML Schema Editor; Document Structure Description; Database schema; XML Schema (W3C); Peer-to-peer; World Wide Web; Database design; XML Encryption","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":[0.0001826312,0.0001040035,0.0001304198,0.00006672172,0.00006908266,0.00003163969,0.0001588347,0.00001715891,0.00001916246],"category_scores_gemma":[0.00002631049,0.00008694734,0.00001719625,0.0001430648,0.00002965756,0.001375856,0.0003916825,0.0000650989,0.00002885086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002066481,"about_ca_system_score_gemma":0.00001751303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002478319,"about_ca_topic_score_gemma":0.001381149,"domain_scores_codex":[0.9991168,0.00003255625,0.0001852984,0.0003311672,0.0001173383,0.0002168353],"domain_scores_gemma":[0.9993919,0.00003909904,0.0000370632,0.0004442449,0.00001537167,0.00007229043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001474625,0.0001407948,0.05799196,0.00008152999,0.00001736349,0.00007468261,0.0007762323,0.0003735485,0.007943332,0.7063722,0.001687739,0.2245259],"study_design_scores_gemma":[0.001263052,0.00007086959,0.03225842,0.0001460525,0.000004303231,0.00019875,0.000307776,0.05061322,0.03657164,0.0002463074,0.8774635,0.0008561642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2144069,0.0005448107,0.7829709,0.0004506147,0.00008820718,0.00009570262,0.00001806583,0.0001032067,0.001321611],"genre_scores_gemma":[0.5298597,0.00007581676,0.4691683,0.0004827676,0.00008661559,0.00001139411,0.000009374678,0.000006512436,0.0002994479],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8757757,"threshold_uncertainty_score":0.354561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0429541083337019,"score_gpt":0.3032750260668475,"score_spread":0.2603209177331456,"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."}}