{"id":"W2027276065","doi":"10.1145/2766905","title":"Practical hex-mesh optimization via edge-cone rectification","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polygon mesh; Hexahedron; Mathematical optimization; Volume mesh; Computer science; Solver; Algorithm; Robustness (evolution); Mathematics; Finite element method; Mesh generation; Geometry","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":[0.0004874253,0.0001487784,0.000120727,0.0003895101,0.0002630436,0.0001563575,0.0003844277,0.000123791,0.00002002297],"category_scores_gemma":[0.000183491,0.0001578534,0.00008024557,0.00153832,0.00004645096,0.0009359598,0.00001172954,0.0002672033,0.00007696784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006996533,"about_ca_system_score_gemma":0.0001957764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001078087,"about_ca_topic_score_gemma":0.00001575397,"domain_scores_codex":[0.9985158,0.0001439942,0.000277336,0.0004138356,0.0004588283,0.0001902242],"domain_scores_gemma":[0.9982995,0.0002502043,0.0001029749,0.0007226505,0.0004387673,0.0001858713],"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":[0.0001135145,0.001254608,0.00004355716,0.00001972826,0.000114742,0.0000129417,0.0009926818,0.7629683,0.001395838,0.06521016,0.006221651,0.1616523],"study_design_scores_gemma":[0.001030781,0.0004893063,0.0003506744,0.00001833229,0.00005450656,0.0001476149,0.00006950158,0.9463523,0.01354181,0.02804955,0.009410503,0.0004851349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008757308,0.00003039456,0.9885585,0.008619885,0.001047847,0.0002072612,0.000003087782,0.0002548367,0.0004024215],"genre_scores_gemma":[0.5462233,0.00007097265,0.4524503,0.0008334529,0.0001003997,0.00005293526,0.00003762242,0.00001380074,0.0002172251],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5453476,"threshold_uncertainty_score":0.6437073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06507108894805766,"score_gpt":0.3049460440448377,"score_spread":0.23987495509678,"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."}}