{"id":"W4416997608","doi":"10.3390/ijgi14120478","title":"An Effective Approach to Geometric and Semantic BIM/GIS Data Integration for Urban Digital Twin","year":2025,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CityGML; 3D city models; Workflow; Scalability; Geospatial analysis; Visualization; Graph; Semantic computing; Semantic grid; Data integration","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001030809,0.0007110691,0.0005360464,0.002868399,0.0007016477,0.002763436,0.001230942,0.0005228758,0.002988244],"category_scores_gemma":[0.002847151,0.0005648392,0.0008320133,0.003304743,0.0007000183,0.003167477,0.004953095,0.00113195,0.001373254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006250169,"about_ca_system_score_gemma":0.001345026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003024385,"about_ca_topic_score_gemma":0.005307594,"domain_scores_codex":[0.9988463,0.0001663095,0.00007687996,0.000199398,0.000640737,0.00007037444],"domain_scores_gemma":[0.9992964,0.00007754589,0.00003870247,0.000315748,0.0002301828,0.0000413683],"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":[0.0001487367,0.0002187049,0.004763081,0.0004017061,0.0001163789,0.0006855414,0.001415755,0.07093592,0.049953,0.1813636,0.01705723,0.6729403],"study_design_scores_gemma":[0.00002704182,0.00009137529,0.003212327,0.00008251858,0.00007111484,0.0008145181,0.001221073,0.6566783,0.05956205,0.1169182,0.1612244,0.00009707295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005187172,0.0000587592,0.9886624,0.00008844133,0.00002813337,0.00009738683,0.0004275392,0.002383484,0.003066589],"genre_scores_gemma":[0.08627935,0.0001340456,0.908487,0.00005394302,0.00001536532,0.0001277715,0.002143425,0.0005712413,0.002187884],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003024385,"threshold_uncertainty_score":0.009996712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00913482431585624,"score_gpt":0.2670926885087299,"score_spread":0.2579578641928736,"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."}}