{"id":"W2046252220","doi":"10.1145/1061347.1061354","title":"ABF++: fast and robust angle based flattening","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":327,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Polygon mesh; Geometry processing; Computer science; Flattening; Conformal map; Algorithm; Parametric statistics; Distortion (music); Speedup; Mathematical optimization; Geometry; Mathematics; Computer graphics (images); Parallel computing","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":[0.00007031373,0.0001268467,0.0001184898,0.0002461477,0.000154779,0.00003487272,0.0001012672,0.00007968229,0.00006191037],"category_scores_gemma":[0.000004531696,0.0001318062,0.00009450789,0.0003325465,0.00002844774,0.00009561465,0.000001173347,0.0002396113,0.00001645615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001639699,"about_ca_system_score_gemma":0.000005179341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001000009,"about_ca_topic_score_gemma":0.0001184794,"domain_scores_codex":[0.9994218,0.00001014905,0.000135247,0.0001502033,0.0001141012,0.0001684961],"domain_scores_gemma":[0.9995652,0.00005368526,0.00001062651,0.0002721247,0.00002420678,0.00007418296],"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":[0.000002322231,0.00002268898,0.00006847432,0.00001237488,0.00004422363,0.000001062548,0.00007074961,0.9534092,0.0002260545,0.00001365047,0.00006301665,0.04606619],"study_design_scores_gemma":[0.0002267958,0.00001809526,0.0001874256,0.00002548598,0.0000752219,0.000002732995,0.00004285419,0.9975404,0.001081862,0.00009220494,0.0005431282,0.0001638018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06632185,0.0001977915,0.9321158,0.0006332285,0.0000602951,0.00003630806,0.0000150865,0.0003226569,0.0002969642],"genre_scores_gemma":[0.9853728,0.0001726331,0.01409023,0.0002105721,0.00003894116,0.000009194618,0.0000057438,0.00002807343,0.00007186208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9190509,"threshold_uncertainty_score":0.5374902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0168071259076753,"score_gpt":0.2071462946680751,"score_spread":0.1903391687603998,"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."}}