{"id":"W2135381699","doi":"10.1145/2601097.2601146","title":"Multimaterial mesh-based surface tracking","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Division of Information and Intelligent Systems; Natural Sciences and Engineering Research Council of Canada; United States-Israel Binational Science Foundation; Intel Corporation; Autodesk; Nvidia; Division of Civil, Mechanical and Manufacturing Innovation; Walt Disney Company","keywords":"Polygon mesh; Robustness (evolution); Computer science; Vertex (graph theory); Triangle mesh; Animation; Topology (electrical circuits); Manifold (fluid mechanics); Surface (topology); Computer animation; T-vertices; Mesh generation; Computational science; Computer graphics (images); Geometry; Theoretical computer science; Mathematics; Graph; Engineering; Finite element method; Mechanical engineering; Combinatorics; Structural engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003981573,0.0002018571,0.0001803211,0.0003176388,0.0003419794,0.0002808498,0.001124951,0.0001235894,0.00001938662],"category_scores_gemma":[0.00002403734,0.000202845,0.0001686012,0.0008833769,0.00006690638,0.0003273279,0.00001665405,0.00021275,0.00001099333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001642662,"about_ca_system_score_gemma":0.00003659413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002665084,"about_ca_topic_score_gemma":0.00001746926,"domain_scores_codex":[0.9985668,0.0001293299,0.0002765467,0.0004378351,0.0003261206,0.0002633411],"domain_scores_gemma":[0.9982945,0.0002432001,0.00008406722,0.001126265,0.0001468376,0.0001051506],"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":[0.00003191195,0.0009004519,0.0003799909,0.00005739215,0.00005680197,0.000004966104,0.0004389034,0.003154623,0.001911526,0.92571,0.0003491336,0.0670043],"study_design_scores_gemma":[0.0006566835,0.0004145819,0.0009884554,0.00005056862,0.00001556125,0.000004849953,0.000003674065,0.920543,0.04226838,0.02875434,0.005881357,0.000418603],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01171887,0.000007738437,0.9859245,0.0006352323,0.0005670452,0.0001552476,0.000006314857,0.0009135584,0.00007143871],"genre_scores_gemma":[0.9113399,0.00002695631,0.08744285,0.001110177,0.00003105871,0.00001425229,0.000004831951,0.00001926306,0.00001065983],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9173883,"threshold_uncertainty_score":0.8271779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799752676678048,"score_gpt":0.2898509280504468,"score_spread":0.2618534012836664,"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."}}