{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002016326,0.0004278453,0.0004250467,0.0002182599,0.00006938961,0.00005293882,0.0005558621,0.0005444227,0.0001033926],"category_scores_gemma":[0.0002654813,0.0005105332,0.0001722293,0.0004152915,0.00005748304,0.0001405869,0.0002227946,0.001236597,0.00004127411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002405421,"about_ca_system_score_gemma":0.00003769188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000032988,"about_ca_topic_score_gemma":0.000009549311,"domain_scores_codex":[0.9985341,0.00004132308,0.0002992598,0.0006033744,0.00008021495,0.0004417031],"domain_scores_gemma":[0.9986866,0.0002916584,0.00009552271,0.0006182458,0.0001450322,0.0001629081],"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":[0.000018558,0.00003139967,0.0001280938,0.0001532613,0.0001157845,0.00001611915,0.00003710673,0.9824826,0.001405939,0.009787179,0.0001064099,0.005717589],"study_design_scores_gemma":[0.0004135402,0.00003478358,0.0002221656,0.00006080724,0.00009525566,8.058825e-7,0.00001881617,0.9757327,0.003243771,0.01739533,0.002214171,0.0005678904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0720296,0.00002222731,0.9234679,0.00001604333,0.002564235,0.000450698,0.00005993722,0.0006715076,0.0007178264],"genre_scores_gemma":[0.8813418,0.00004457701,0.1178133,0.00002342732,0.0002612867,0.00001127631,0.00009381478,0.00009986852,0.0003106501],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8093122,"threshold_uncertainty_score":0.9997346,"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."}}