{"id":"W1542136675","doi":"","title":"Effective order strong stability preserving Runge–Kutta methods","year":2012,"lang":"en","type":"preprint","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; King Abdullah University of Science and Technology","keywords":"Runge–Kutta methods; Order (exchange); Stability (learning theory); Applied mathematics; Mathematics; Set (abstract data type); Mathematical optimization; Construct (python library); Computer science; Numerical analysis; Mathematical analysis; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006553505,0.0008157714,0.001741722,0.001653881,0.001570374,0.00009617583,0.004146113,0.0007813909,0.001818231],"category_scores_gemma":[0.00317751,0.001024094,0.0009822396,0.001810923,0.002201295,0.0008940944,0.01382993,0.004531302,0.00001718807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00136914,"about_ca_system_score_gemma":0.0009939976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003051704,"about_ca_topic_score_gemma":0.002046932,"domain_scores_codex":[0.9844659,0.009651208,0.0005372142,0.001632357,0.001818833,0.001894507],"domain_scores_gemma":[0.9838939,0.009707373,0.000855875,0.002645727,0.001848213,0.001048885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01021668,0.009857441,0.04485655,0.01671906,0.0103286,0.0004743017,0.05747883,0.0006725257,0.01689882,0.3866271,0.007359788,0.4385103],"study_design_scores_gemma":[0.004102167,0.001043024,0.02959738,0.001186829,0.001796589,0.00001077025,0.03177502,0.01060707,0.001224018,0.8022811,0.1138951,0.002480938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1163092,0.0001071436,0.8450451,0.0005308979,0.0004816595,0.003443454,0.001209687,0.0002705149,0.03260233],"genre_scores_gemma":[0.06769991,0.0004650963,0.9283231,0.000006981664,0.0002178718,0.000005321309,0.0003279262,0.0001283005,0.002825425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4360294,"threshold_uncertainty_score":0.9997295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1212499627140624,"score_gpt":0.3865574240698482,"score_spread":0.2653074613557858,"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."}}