{"id":"W1980789236","doi":"10.1145/1342250.1342281","title":"Precise vector textures for real-time 3D rendering","year":2008,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ontario Centres of Excellence","keywords":"Vector graphics; Computer science; Rendering (computer graphics); Raster graphics; Vector field; Parametric equation; Scalable Vector Graphics; Computer vision; Digital geometry; Texture mapping; Artificial intelligence; Graphics; Computer graphics (images); Algorithm; Mathematics; Image processing; Geometry; Digital image; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005712436,0.0009763183,0.0006370221,0.0008033289,0.0004778994,0.002743237,0.001195871,0.0007367416,0.0255011],"category_scores_gemma":[0.003973071,0.0006279674,0.000534714,0.00120932,0.0005055614,0.002221853,0.001581139,0.001526161,0.005624732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005683324,"about_ca_system_score_gemma":0.0005234291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008494739,"about_ca_topic_score_gemma":0.001321109,"domain_scores_codex":[0.9992201,0.0001051557,0.000055118,0.00006092535,0.0005071778,0.00005141082],"domain_scores_gemma":[0.9988503,0.0003373874,0.00006989435,0.0004358157,0.0002403638,0.00006616223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003588593,0.00007286623,0.0006899162,0.0005910425,0.00004930601,0.0002675109,0.0003476535,0.03596264,0.1088142,0.1621665,0.06609762,0.6245819],"study_design_scores_gemma":[0.0001588797,0.0001271082,0.0009678589,0.0001262922,0.00003841345,0.001001855,0.000123511,0.4747221,0.0869078,0.09239095,0.3433118,0.0001234131],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002349088,0.0004285914,0.982219,0.0001459237,0.0001635294,0.00006458988,0.0002785365,0.007796678,0.006553979],"genre_scores_gemma":[0.1160344,0.001409025,0.8671881,0.0001269229,0.0001552587,0.0002157452,0.001270734,0.003758576,0.009841191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0255011,"threshold_uncertainty_score":0.08530968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920093913119806,"score_gpt":0.28714691705609,"score_spread":0.2579459779248919,"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."}}