{"id":"W2949761760","doi":"10.48550/arxiv.1003.0495","title":"Numerical integration for high order pyramidal finite elements","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Numerical methods in engineering","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Finite element method; Numerical integration; Piecewise; Mathematics; Polynomial; Space (punctuation); Convergence (economics); Quadrature (astronomy); Extended finite element method; Order (exchange); Rational function; Rule of thumb; Mathematical analysis; Piecewise linear function; Computer science; Algorithm; Engineering; Structural engineering; Electronic engineering","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":[0.001015172,0.0004127204,0.0005370954,0.0003519543,0.0004164866,0.0009669127,0.0006769329,0.0007889884,0.002083109],"category_scores_gemma":[0.005203281,0.0002521273,0.0005485551,0.0004898354,0.001209692,0.0009862417,0.001739773,0.001258098,0.0005678312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005919291,"about_ca_system_score_gemma":0.0005293405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241841,"about_ca_topic_score_gemma":0.001114756,"domain_scores_codex":[0.9992482,0.000161659,0.00003551967,0.000070698,0.0004212045,0.00006275735],"domain_scores_gemma":[0.9988087,0.0006238299,0.0001076448,0.0002109639,0.0002004847,0.00004830743],"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":[0.0000883036,0.00004006764,0.0008089798,0.0001977033,0.00003369822,0.0001770314,0.0002447622,0.593106,0.0267606,0.3273415,0.001265225,0.04993612],"study_design_scores_gemma":[0.000006501186,0.00002120647,0.0001003355,0.00001547435,0.000005142818,0.00004959395,0.00001440099,0.9674569,0.003805303,0.02635617,0.002162496,0.000006454933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02084135,0.000317112,0.9707845,0.0001431502,0.00005161927,0.00001943445,0.00002661768,0.0001385155,0.007677713],"genre_scores_gemma":[0.4378636,0.0006603042,0.5568171,0.0001285781,0.00004349064,0.00007679678,0.00008477095,0.0001920934,0.004133374],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002083109,"threshold_uncertainty_score":0.006968737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04929063163615645,"score_gpt":0.2074754510510788,"score_spread":0.1581848194149224,"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."}}