{"id":"W2419929067","doi":"10.1007/978-3-319-12307-3_47","title":"Recent Advances in Error Control B-spline Gaussian Collocation Software for PDEs","year":2015,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Collocation (remote sensing); Computation; Orthogonal collocation; Collocation method; Computer science; Software; Gaussian; Algorithm; Partial differential equation; Overhead (engineering); Spline (mechanical); Applied mathematics; Mathematical optimization; Mathematics; Differential equation; Mathematical analysis; Ordinary differential equation; 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":[0.001945992,0.0007971727,0.001527427,0.001424655,0.0003530236,0.001754763,0.001987388,0.001744346,0.006239586],"category_scores_gemma":[0.004392297,0.000776975,0.0009746351,0.003252287,0.001249406,0.001813174,0.002295044,0.002654643,0.003678591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006002623,"about_ca_system_score_gemma":0.001160961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002468764,"about_ca_topic_score_gemma":0.001886149,"domain_scores_codex":[0.9983809,0.0002859194,0.000133152,0.0002378842,0.0008987861,0.00006327384],"domain_scores_gemma":[0.9971735,0.001338409,0.0001073717,0.0003156505,0.0009511842,0.0001137915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009271301,0.00008704541,0.000348519,0.001404755,0.00007027124,0.00005869534,0.0002374891,0.044401,0.008421137,0.09123809,0.01289066,0.8407496],"study_design_scores_gemma":[0.00004014018,0.0001715597,0.0008239361,0.000645148,0.00009234641,0.0003164415,0.00008812033,0.4996404,0.0116498,0.1029981,0.3834064,0.0001276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002663285,0.04991781,0.9381402,0.0005273228,0.000731771,0.00002397356,0.00007715193,0.0008910965,0.007027256],"genre_scores_gemma":[0.07760374,0.09785812,0.7878448,0.000910246,0.001957905,0.0001456064,0.0007721205,0.001982354,0.03092511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006239586,"threshold_uncertainty_score":0.02087355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09047400671809619,"score_gpt":0.3762329178272819,"score_spread":0.2857589111091857,"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."}}