{"id":"W4414317208","doi":"10.5194/isprs-archives-xlviii-4-w15-2025-135-2025","title":"An OGC API–Based Framework for Scalable and Interoperable Urban Digital Twin Ecosystems: Insights from the OGC Urban Digital Twins Interoperability Pilot","year":2025,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Interoperability; Geospatial analysis; Scalability; 3D city models; Sensor web; Modular design; Data exchange; Data modeling","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000918042,0.0004705926,0.0004470316,0.0006328198,0.001167213,0.002680048,0.001753852,0.0001165428,0.000005075516],"category_scores_gemma":[0.0008617835,0.0002847331,0.0002899498,0.0008082624,0.002514254,0.001475451,0.0005103025,0.0005407233,0.000002629685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007541802,"about_ca_system_score_gemma":0.0001942405,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2686425,"about_ca_topic_score_gemma":0.05091839,"domain_scores_codex":[0.9962625,0.0002027672,0.001504986,0.0004112416,0.001147369,0.0004711547],"domain_scores_gemma":[0.9960417,0.002197571,0.0007174481,0.0005854228,0.0002965989,0.0001613061],"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":[0.0002140138,0.00003497702,0.0006660394,0.00008118542,0.0001356542,1.218876e-7,0.003826508,0.006858866,0.0005939637,0.00005056235,0.0001446252,0.9873935],"study_design_scores_gemma":[0.0007487595,0.0001749853,0.001487078,0.0007409088,0.0000388953,0.00002165594,0.003566734,0.9702584,0.00418424,0.01093321,0.007534618,0.0003105233],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0335706,0.00005195639,0.9487323,0.001950182,0.002196196,0.0009344962,0.0004966638,0.00009833011,0.01196934],"genre_scores_gemma":[0.9968634,0.00004030014,0.001852489,0.0008776088,0.0001772514,0.000001567376,0.0001157572,0.0000168337,0.00005483051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.987083,"threshold_uncertainty_score":0.9999605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650769544191596,"score_gpt":0.2445770937876781,"score_spread":0.2280693983457621,"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."}}