{"id":"W4410359771","doi":"10.1016/j.isprsjprs.2025.04.026","title":"Building LOD representation for 3D urban scenes","year":2025,"lang":"en","type":"article","venue":"ISPRS Journal of Photogrammetry and Remote Sensing","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Shenzhen Science and Technology Innovation Program; Basic and Applied Basic Research Foundation of Guangdong Province; National Key Research and Development Program of China; Shenzhen University; National Natural Science Foundation of China","keywords":"Representation (politics); Computer science; Computer graphics (images); Geography; Artificial intelligence; Political 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002607284,0.0001107923,0.0002026743,0.0002585126,0.0001208757,0.00006453868,0.00007029359,0.00007941361,7.57407e-7],"category_scores_gemma":[0.0001156176,0.0001069976,0.00009181676,0.0003177964,0.00003557157,0.00008427501,0.00001683681,0.0001762761,2.652496e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004048393,"about_ca_system_score_gemma":0.00002144188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009444872,"about_ca_topic_score_gemma":0.00001824459,"domain_scores_codex":[0.9992254,0.00001750301,0.0003748977,0.0001105716,0.0001013787,0.0001702833],"domain_scores_gemma":[0.9993588,0.0001726569,0.0001016719,0.0001244633,0.0001821718,0.00006019727],"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":[0.00002459514,0.000009034162,0.00008160647,0.0001219121,0.0001027881,0.000003641328,0.0001577737,0.02023721,0.08795244,0.0001056458,0.0004424202,0.890761],"study_design_scores_gemma":[0.0005111507,0.00003217789,0.0001265927,0.0003313936,0.0001072895,0.00007820813,0.0001078892,0.9174774,0.07111359,0.004519139,0.005461414,0.00013374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1032563,0.000782639,0.8949254,0.0001093644,0.0005226907,0.0001494147,0.000001706663,0.00004634211,0.0002061399],"genre_scores_gemma":[0.5583273,0.0001182081,0.4413259,0.00004233813,0.0001546971,8.551881e-8,0.000001052398,0.00001362218,0.0000168118],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8972402,"threshold_uncertainty_score":0.4363237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01238517543650579,"score_gpt":0.2809983457429336,"score_spread":0.2686131703064278,"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."}}