{"id":"W2890600889","doi":"10.5194/isprs-annals-iv-4-89-2018","title":"A SEMANTIC GRAPH DATABASE FOR BIM-GIS INTEGRATED INFORMATION MODEL FOR AN INTELLIGENT URBAN MOBILITY WEB APPLICATION","year":2018,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Graph database; RDF; Database; Information retrieval; Semantic Web; Graph; Theoretical computer science","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":[0.001247878,0.0007033173,0.0006640687,0.003115981,0.0009018247,0.004159462,0.002464356,0.001080766,0.00590745],"category_scores_gemma":[0.001875835,0.0004141631,0.001140813,0.003004662,0.0006095623,0.003559443,0.002117525,0.001045284,0.002609079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156511,"about_ca_system_score_gemma":0.00235813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0147147,"about_ca_topic_score_gemma":0.01432284,"domain_scores_codex":[0.9989466,0.000187686,0.0001508291,0.0002072798,0.0004345727,0.00007300632],"domain_scores_gemma":[0.9993079,0.00009818409,0.00004783659,0.0002337493,0.0002525698,0.00005973806],"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":[0.0006188466,0.0006929702,0.008932726,0.001062471,0.0002929074,0.002803514,0.001688581,0.1191119,0.02118759,0.4311045,0.1048494,0.3076544],"study_design_scores_gemma":[0.00009475063,0.00008141076,0.001929173,0.0002307944,0.0001582911,0.0007748518,0.0006776596,0.5006273,0.02251376,0.07527631,0.3975041,0.0001316416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01764464,0.0004759011,0.9152607,0.001027934,0.0001967716,0.0007502299,0.01270286,0.02907335,0.02286764],"genre_scores_gemma":[0.2302552,0.001147804,0.6953498,0.0005652832,0.00006297448,0.001092245,0.05320303,0.002330165,0.01599353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0147147,"threshold_uncertainty_score":0.02925807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08048115437673738,"score_gpt":0.3364964460364934,"score_spread":0.256015291659756,"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."}}