{"id":"W165101881","doi":"10.11575/prism/30305","title":"AUTOMATIC INTEGRATION OF RELATIONAL DATABASE SCHEMAS","year":2000,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Manitoba","funders":"","keywords":"Computer science; Data integration; Metadata; Information retrieval; Database; IDEF1X; Data element; Information integration; Relational database; Schema (genetic algorithms); Semantic integration; Data architecture; Data mapping; World Wide Web; Ontology-based data integration; Semantic Web; Semantic Web Stack; Reference architecture; Programming language; Software architecture; Software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008681192,0.0008128068,0.001287708,0.004188916,0.000967109,0.005585979,0.002263845,0.001063066,0.003482418],"category_scores_gemma":[0.01813066,0.001132996,0.002031824,0.003503016,0.0006676291,0.005832726,0.004604584,0.00193285,0.002186048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001108335,"about_ca_system_score_gemma":0.002118755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002610828,"about_ca_topic_score_gemma":0.003037864,"domain_scores_codex":[0.9895215,0.00235751,0.001345,0.001485349,0.004965737,0.0003248776],"domain_scores_gemma":[0.9877537,0.003104554,0.0006520802,0.004443289,0.003807904,0.000238447],"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":[0.0004862401,0.0004809828,0.009957191,0.0007720664,0.0005139649,0.001374044,0.003216919,0.02509407,0.03982504,0.1460556,0.01997339,0.7522504],"study_design_scores_gemma":[0.0002170315,0.0002401259,0.004709184,0.0006385806,0.0004406796,0.00161699,0.002297927,0.5151859,0.1401597,0.1163394,0.2179255,0.0002289768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02226943,0.0007257319,0.9518761,0.0002869585,0.0001073353,0.0004805084,0.0009001856,0.01701855,0.006335188],"genre_scores_gemma":[0.1141863,0.0005356009,0.8753215,0.0001816129,0.00003560578,0.0001706083,0.005132159,0.001525962,0.002910713],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008681192,"threshold_uncertainty_score":0.04591107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194045954024642,"score_gpt":0.2096516951244115,"score_spread":0.1902470997219473,"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."}}