{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001838442,0.00004811011,0.00006787859,0.0001898669,0.00003778484,0.00006339998,0.0004878185,0.00003147988,0.000006716859],"category_scores_gemma":[0.00001870782,0.0000414954,0.00003522502,0.000988755,0.00000895793,0.0002638151,0.0002882348,0.00003055215,0.000005875586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003797739,"about_ca_system_score_gemma":0.00001316883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008220948,"about_ca_topic_score_gemma":0.000002937004,"domain_scores_codex":[0.9995095,0.00002056753,0.00009121897,0.0001354378,0.0001574465,0.00008581658],"domain_scores_gemma":[0.9994965,0.00004800088,0.00004599387,0.0003000295,0.00008666895,0.00002280048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.835252e-7,0.000008272615,0.002257183,0.0000149043,0.000004011115,5.725951e-7,0.0003037839,0.000008411034,0.0003055499,0.9083762,0.08464662,0.004074178],"study_design_scores_gemma":[0.00007639937,0.00004454143,0.01727763,0.00003008781,0.000001541213,0.000001162159,0.00001320563,0.9032225,0.02595728,0.0373889,0.01587971,0.0001070394],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006326167,0.00003037278,0.9898072,0.0007510514,0.00008328801,0.00007327359,5.060002e-7,0.0007686829,0.002159438],"genre_scores_gemma":[0.9264431,0.00005687616,0.07164821,0.0001748952,0.0000382054,0.00001169194,0.000008450593,0.000007555084,0.001611005],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.920117,"threshold_uncertainty_score":0.1692133,"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."}}