{"id":"W2138685411","doi":"10.1109/tmag.2007.914827","title":"An Adaptive Remeshing Technique Ensuring High Quality Meshes","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Polygon mesh; Computer science; Bubble; Quality (philosophy); Computational science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004965293,0.0005653584,0.0004109667,0.0007805891,0.0004419996,0.0004717939,0.0009747359,0.0007850126,0.004207045],"category_scores_gemma":[0.001817185,0.0003665555,0.000504776,0.0005289773,0.0004934721,0.000883508,0.001050071,0.0009407403,0.001557051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595303,"about_ca_system_score_gemma":0.0003354482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004947081,"about_ca_topic_score_gemma":0.0006027395,"domain_scores_codex":[0.9994585,0.00008704578,0.00002642241,0.00007799854,0.0003122957,0.00003768869],"domain_scores_gemma":[0.9994549,0.0001947239,0.00005273385,0.0001429242,0.0001311434,0.00002345245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001626195,0.00004372173,0.0006277495,0.0005436829,0.00006153597,0.0005673619,0.0004584093,0.03547676,0.5241347,0.04484749,0.006144441,0.3869315],"study_design_scores_gemma":[0.00009875995,0.0005776563,0.00181748,0.0001580752,0.0001343868,0.00512474,0.000172785,0.4899054,0.2996608,0.01969413,0.1825051,0.0001507527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005333297,0.0003378784,0.9904208,0.00009092104,0.00007304053,0.00005611957,0.00002722802,0.0004932578,0.003167309],"genre_scores_gemma":[0.09190954,0.0007795719,0.900066,0.0001469113,0.0001085363,0.0001226694,0.0001132412,0.0003263715,0.006427158],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004207045,"threshold_uncertainty_score":0.01407397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04624943060061796,"score_gpt":0.2780174412051399,"score_spread":0.231768010604522,"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."}}