{"id":"W4403531319","doi":"10.5194/isprs-annals-x-4-2024-419-2024","title":"The Concept of Levels of Detail for 3D Niche Models in CityGML","year":2024,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Natural Science Foundation of China","keywords":"Niche; CityGML; Computer science; Biology; Ecology; Data mining; Visualization","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":[0.0009761959,0.0006075797,0.0005058807,0.002510193,0.0006466959,0.004751882,0.001254413,0.001093313,0.002327913],"category_scores_gemma":[0.003100571,0.0007301926,0.001639046,0.002197512,0.001554377,0.002431775,0.003637419,0.00113906,0.0008866329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001432414,"about_ca_system_score_gemma":0.0008811863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00814302,"about_ca_topic_score_gemma":0.01095018,"domain_scores_codex":[0.998882,0.0002465564,0.0001041301,0.0001588891,0.000479538,0.0001289325],"domain_scores_gemma":[0.9987726,0.0004042645,0.0001149291,0.0004340162,0.0001948101,0.00007946248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002812656,0.0001172704,0.01967879,0.001276961,0.0001701829,0.001194705,0.005564391,0.3861431,0.02754323,0.3023019,0.01658405,0.2391441],"study_design_scores_gemma":[0.00003764532,0.00008006324,0.01087075,0.0003759477,0.00008332678,0.001089905,0.001912859,0.6840419,0.01482424,0.0679958,0.2184795,0.0002080911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04564876,0.0003746208,0.9358744,0.0003155325,0.00006061654,0.0001752792,0.002624609,0.003543861,0.01138246],"genre_scores_gemma":[0.4526705,0.0004686281,0.5379393,0.0001284748,0.00002068254,0.0002625121,0.005220737,0.0007045891,0.002584596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00814302,"threshold_uncertainty_score":0.01619124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06577117533019829,"score_gpt":0.3079705122871931,"score_spread":0.2421993369569949,"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."}}