{"id":"W4206302443","doi":"10.1093/imanum/drab103","title":"Numerical analysis of the LDG method for large deformations of prestrained plates","year":2021,"lang":"en","type":"article","venue":"IMA Journal of Numerical Analysis","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Science Foundation","keywords":"Mathematics; Discretization; Constraint (computer-aided design); Balanced flow; Initialization; Metric (unit); Numerical analysis; Convergence (economics); Flow (mathematics); Boundary (topology); Nonlinear system; Applied mathematics; Stability (learning theory); Mathematical analysis; Geometry; Computer science; Physics","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":[0.001102327,0.0005479849,0.0005579109,0.000772705,0.0004322079,0.0007379123,0.0009792933,0.001350806,0.001803972],"category_scores_gemma":[0.002381482,0.00026021,0.0003077513,0.0003809448,0.001870509,0.0004589398,0.0009661746,0.0008768472,0.0001954604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008717352,"about_ca_system_score_gemma":0.0007084818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004677922,"about_ca_topic_score_gemma":0.002853981,"domain_scores_codex":[0.9997435,0.00009501873,0.00001063291,0.00002134549,0.0001016754,0.00002778876],"domain_scores_gemma":[0.99893,0.0006649302,0.00009141013,0.00009023245,0.0001438762,0.00007950352],"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":[0.00008462169,0.00003902721,0.0007661242,0.00004749962,0.00001096422,0.000102622,0.00005819803,0.9820035,0.005176393,0.007013562,0.0001956365,0.004501851],"study_design_scores_gemma":[0.000004548412,0.000008909411,0.00005329856,0.000002724807,7.293627e-7,0.000005028626,0.000005340696,0.998991,0.000429559,0.0004131788,0.00008365935,0.000002042371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3779728,0.0005653441,0.6064879,0.0009487074,0.000133142,0.0001589306,0.0001504567,0.0007494401,0.01283331],"genre_scores_gemma":[0.9050171,0.0000860588,0.09194162,0.00008166374,0.00001528376,0.00009253962,0.00006229374,0.00009775827,0.002605706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004677922,"threshold_uncertainty_score":0.009301364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02205683802736581,"score_gpt":0.3431241611416336,"score_spread":0.3210673231142678,"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."}}