{"id":"W2086134854","doi":"10.1109/mis.2010.17","title":"Converting a Historical Architecture Encyclopedia into a Semantic Knowledge Base","year":2010,"lang":"en","type":"article","venue":"IEEE Intelligent Systems","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Encyclopedia; Computer science; Knowledge base; Architecture; World Wide Web; Task (project management); Data science; Engineering; Library science; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001298362,0.001374261,0.0008267794,0.0386418,0.001590414,0.007582496,0.001522033,0.0009808537,0.04240308],"category_scores_gemma":[0.00538611,0.0008118702,0.0006655387,0.04001559,0.0009443635,0.008478846,0.002435039,0.001730597,0.02349033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00181939,"about_ca_system_score_gemma":0.003818974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01029782,"about_ca_topic_score_gemma":0.01977785,"domain_scores_codex":[0.9989777,0.0001284541,0.0002873878,0.0001693725,0.0003786114,0.00005854568],"domain_scores_gemma":[0.996759,0.0009193741,0.0002258899,0.0006737885,0.001285741,0.000136188],"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":[0.00007337037,0.00009913331,0.001108099,0.003290605,0.0001039644,0.001057496,0.001565455,0.003255257,0.00569734,0.05403252,0.3850289,0.5446879],"study_design_scores_gemma":[0.000007025716,0.000008182012,0.001192584,0.0004477286,0.00003024694,0.0002758419,0.0006838107,0.000851928,0.001098568,0.006675216,0.9887051,0.00002375912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01200138,0.01466793,0.200804,0.0039678,0.004644236,0.0008018781,0.327251,0.02290255,0.4129592],"genre_scores_gemma":[0.04951391,0.03384058,0.400902,0.001627359,0.001227053,0.001240576,0.405829,0.007491128,0.09832846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04240308,"threshold_uncertainty_score":0.1418524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061444974907163,"score_gpt":0.2586262234999543,"score_spread":0.2380117737508827,"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."}}