{"id":"W2165716721","doi":"10.1145/641480.641506","title":"Budget sampling of parametric surface patches","year":2003,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia","keywords":"Computer science; Parametric surface; Rendering (computer graphics); Memory footprint; Computer graphics (images); Spline (mechanical); Parametric statistics; Workstation; Sampling (signal processing); Surface (topology); Computer graphics; Point (geometry); Parametric model; Graphics; Algorithm; Computer vision; Mathematics; Statistics; Geometry; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008183039,0.0007040033,0.0008676763,0.001049676,0.0003083187,0.001284549,0.001273895,0.000807791,0.01216622],"category_scores_gemma":[0.005811013,0.0005212298,0.000570627,0.001196451,0.0005053378,0.00167216,0.001559648,0.001001219,0.002979899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005109875,"about_ca_system_score_gemma":0.0006678498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002954139,"about_ca_topic_score_gemma":0.005493222,"domain_scores_codex":[0.9992946,0.0001649533,0.00002938422,0.0001422948,0.0002871543,0.00008148198],"domain_scores_gemma":[0.9986755,0.000445478,0.00005887707,0.0004915516,0.0002406593,0.00008791385],"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":[0.0009998857,0.0001532277,0.003861804,0.0004423195,0.0001222934,0.0001599216,0.0002257872,0.2366467,0.06105513,0.06460189,0.02387264,0.6078584],"study_design_scores_gemma":[0.00002361291,0.00004626059,0.0007420423,0.00001798635,0.00001046618,0.00009355524,0.00004002715,0.9698602,0.009288555,0.01269893,0.007163159,0.00001525095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03011107,0.0002286123,0.9605879,0.0001428763,0.0000763419,0.0000647964,0.0004720143,0.001281789,0.007034509],"genre_scores_gemma":[0.4901292,0.0005268757,0.4872654,0.0001840887,0.0001161071,0.0002458682,0.003929321,0.00206256,0.01554058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01216622,"threshold_uncertainty_score":0.04070002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03983742341398441,"score_gpt":0.3061152000075739,"score_spread":0.2662777765935894,"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."}}