{"id":"W2404523947","doi":"","title":"Towards Semantic Integration of Legacy Databases for Homeland Security.","year":2005,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science; Metadata; Ontology; World Wide Web; Context (archaeology); Vocabulary; Database; Homeland security; Semantic Web; Information retrieval","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":[0.0004858216,0.0001443043,0.0002021672,0.0002025057,0.0001017577,0.0001556725,0.0006311291,0.00005731687,0.0000608015],"category_scores_gemma":[0.0008259748,0.0001264992,0.00007480583,0.0002772926,0.0001087191,0.0007521734,0.00007783136,0.0001137461,0.00007012107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000495639,"about_ca_system_score_gemma":0.0002809358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007085622,"about_ca_topic_score_gemma":0.000393935,"domain_scores_codex":[0.998446,0.00004452817,0.0004331743,0.000356282,0.000518951,0.0002010706],"domain_scores_gemma":[0.9983701,0.0003549988,0.0001607542,0.0002608757,0.0008028902,0.00005039161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002608154,0.0001023937,0.00001001013,0.00001001989,0.000006834172,4.480908e-7,0.0003504177,0.0002015117,0.00134935,0.7888897,0.0001651896,0.208888],"study_design_scores_gemma":[0.00005325832,0.0001659786,0.0003665292,0.00006501148,0.000006290595,0.000003918215,0.0003219765,0.4198121,0.2433852,0.3345493,0.001078532,0.0001919067],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01410763,0.00005314391,0.9742427,0.004406152,0.0003003122,0.000266664,0.00003463725,0.00007956698,0.006509128],"genre_scores_gemma":[0.9654461,0.00002866313,0.03400917,0.0002572515,0.0001483138,0.00003016873,0.0000245801,0.000004854204,0.00005094634],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9513384,"threshold_uncertainty_score":0.5158487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1757340789809956,"score_gpt":0.3787654694567645,"score_spread":0.2030313904757689,"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."}}