{"id":"W2800542763","doi":"10.1139/tcsme-2003-0018","title":"EVALUATION OF COMBINED DELAUNAY TRIANGULATION AND REMESHING FOR FINITE ELEMENT ANALYSIS OF CONDUCTIVE HEAT TRANSFER","year":2004,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Delaunay triangulation; Finite element method; Thermal conduction; Triangulation; Heat transfer; Constrained Delaunay triangulation; Bowyer–Watson algorithm; Transient (computer programming); Polygon mesh; Steady state (chemistry); Mathematics; Applied mathematics; Mathematical optimization; Algorithm; Mechanics; Mathematical analysis; Computer science; Geometry; Structural engineering; Physics; Thermodynamics; Engineering; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008911062,0.00006586164,0.0001667536,0.0001354153,0.00009958884,0.000009632372,0.0001226709,0.00005593747,0.000003208252],"category_scores_gemma":[0.00006525937,0.0000633422,0.00036162,0.0006639384,0.00001464715,0.0001309603,0.000002814772,0.00004525992,1.006214e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001940934,"about_ca_system_score_gemma":0.0002569795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001126391,"about_ca_topic_score_gemma":0.004730562,"domain_scores_codex":[0.9992514,0.00001687312,0.0002610331,0.0001275265,0.0002428298,0.0001003045],"domain_scores_gemma":[0.9992548,0.0001516829,0.00003019785,0.0001335004,0.0003747713,0.00005500199],"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":[0.000005425461,0.00001467132,5.868556e-7,0.00002730323,0.0004521198,3.769903e-9,0.0004449782,0.9597308,0.01377522,0.02376157,0.000001047906,0.001786254],"study_design_scores_gemma":[0.0009400682,0.00007924681,0.0001197215,0.00001737042,0.0008793859,2.064718e-7,0.00004251892,0.9298164,0.06561509,0.002419563,0.00001537323,0.00005511528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06628415,0.00004991854,0.9325762,0.000403685,0.0001003868,0.0004965618,0.00008078932,0.00000700335,0.000001355884],"genre_scores_gemma":[0.940011,0.000002928935,0.05989428,0.00001926836,0.000006209073,0.0000437911,0.00001582612,0.000004328681,0.000002406794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8737268,"threshold_uncertainty_score":0.2639765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03080094572191765,"score_gpt":0.253776788179839,"score_spread":0.2229758424579213,"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."}}