{"id":"W4387829394","doi":"10.1109/igarss52108.2023.10282299","title":"Feature Preserving Decimation of Urban Meshes","year":2023,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Saint Mary's University","funders":"","keywords":"Computer science; Polygon mesh; Decimation; Feature (linguistics); Feature extraction; Point cloud; Rendering (computer graphics); Lidar; 3D modeling; Data mining; Computational science; Bandwidth (computing); Artificial intelligence; Computer graphics (images); Remote sensing","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":[0.0001575394,0.0004244442,0.0003428573,0.0005184717,0.0001724618,0.0005168297,0.0003592399,0.0002827923,0.001842003],"category_scores_gemma":[0.0009129272,0.0001979872,0.0003999273,0.0004639454,0.0002326218,0.0004639218,0.0005828608,0.0005138487,0.0004774232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001789421,"about_ca_system_score_gemma":0.0002144064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001115485,"about_ca_topic_score_gemma":0.002111246,"domain_scores_codex":[0.99988,0.00001605753,0.000005945358,0.00002094511,0.0000596616,0.00001735604],"domain_scores_gemma":[0.9997463,0.00007826425,0.00002938121,0.00008951245,0.00004382746,0.00001266652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002283502,0.00005853123,0.002081192,0.0002028759,0.00004480556,0.0005328147,0.0004524804,0.4536378,0.1158262,0.01902409,0.003398838,0.404512],"study_design_scores_gemma":[0.00000676642,0.00004250511,0.0007968671,0.000008381175,0.000006497373,0.0002098087,0.00007346248,0.9637631,0.02407076,0.005339831,0.005672639,0.000009468392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.135018,0.0001570853,0.8591985,0.00009741304,0.00004893202,0.00005250752,0.0002551517,0.001314659,0.003857816],"genre_scores_gemma":[0.6991811,0.0002575844,0.2948133,0.00006407558,0.00002874906,0.00004964664,0.0007753405,0.0003992569,0.004430898],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001842003,"threshold_uncertainty_score":0.006162107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319682120158927,"score_gpt":0.2953769211015446,"score_spread":0.2721800998999553,"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."}}