{"id":"W2138794734","doi":"10.1109/icde.2006.88","title":"Making Designer Schemas with Colors","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Schema (genetic algorithms); XML; Intuition; Data redundancy; Redundancy (engineering); Information retrieval; Theoretical computer science; Data mining; XML Schema (W3C); Document Structure Description; Programming language; Database; Document type definition; 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":[0.00006687536,0.00007001048,0.0000738762,0.00002900803,0.00007904054,0.00002854972,0.0001245167,0.00001544566,0.00001832794],"category_scores_gemma":[0.00000327774,0.00004568783,0.00001255203,0.00017289,0.00002803673,0.0004925162,0.00006962751,0.00003206762,0.00003927052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001289286,"about_ca_system_score_gemma":0.00002439879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007421309,"about_ca_topic_score_gemma":0.0001084625,"domain_scores_codex":[0.9994388,0.00001177139,0.00008949964,0.0001850468,0.0001224844,0.000152378],"domain_scores_gemma":[0.9996107,0.00002225946,0.00003520571,0.0002801149,0.00003251804,0.00001916299],"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":[0.000002313352,0.000009020073,0.0005425768,0.000004152361,0.000002021545,0.00001915266,0.0000187697,0.000186238,0.0008594045,0.99598,0.001382215,0.0009941326],"study_design_scores_gemma":[0.0007673168,0.0002147505,0.003742441,0.0001132127,0.00000622059,0.0001936862,0.0001473677,0.01501982,0.04979229,0.003255691,0.9260153,0.0007319151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003223052,0.0000389846,0.9656196,0.0001350224,0.00004592676,0.00006666285,7.499578e-7,0.0001719002,0.03069816],"genre_scores_gemma":[0.2649037,2.952326e-7,0.7329407,0.0001200961,0.00003740098,0.000009096435,0.000001199046,0.000004215829,0.001983279],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9927243,"threshold_uncertainty_score":0.1863096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104230506838537,"score_gpt":0.2459990558829333,"score_spread":0.224956750814548,"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."}}