{"id":"W2036522227","doi":"10.1103/physreve.70.017701","title":"Numerical methods for stochastic differential equations","year":2004,"lang":"en","type":"article","venue":"Physical Review E","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Stochastic differential equation; Numerical stability; Numerical partial differential equations; Applied mathematics; Stochastic partial differential equation; Differential equation; Stability (learning theory); Numerical integration; Mathematics; Order of accuracy; Numerical analysis; Computer science; Backward differentiation formula; Differential algebraic equation; Mathematical optimization; Mathematical analysis; Ordinary differential equation","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":[0.003721461,0.001578428,0.002206044,0.002071836,0.0008312798,0.002326668,0.002187109,0.002505891,0.009707289],"category_scores_gemma":[0.01442998,0.0005674504,0.001505098,0.002532341,0.001827253,0.002111554,0.002612613,0.004889302,0.004374589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378584,"about_ca_system_score_gemma":0.002144406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002385056,"about_ca_topic_score_gemma":0.001578727,"domain_scores_codex":[0.9968848,0.001370101,0.000237171,0.0002278175,0.001171131,0.0001089144],"domain_scores_gemma":[0.9950923,0.002899961,0.0003541608,0.0004789848,0.00104818,0.0001264408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003276796,0.00005739604,0.0003951333,0.0009557343,0.0001189486,0.0001363856,0.0002091658,0.1335957,0.00187988,0.7632802,0.01523073,0.08410798],"study_design_scores_gemma":[0.0000478785,0.0000284487,0.0002012005,0.0002528537,0.0000287978,0.0001140805,0.00004590492,0.4611163,0.0006235426,0.4507551,0.08674776,0.0000380267],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007254961,0.007235404,0.9782158,0.0009524709,0.0007800945,0.0001921671,0.0002706197,0.0005358643,0.01109203],"genre_scores_gemma":[0.05155143,0.01236905,0.9127198,0.000817067,0.001717871,0.002083697,0.0007478664,0.0008760037,0.01711718],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009707289,"threshold_uncertainty_score":0.03247416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06297209495944618,"score_gpt":0.3643715865364968,"score_spread":0.3013994915770506,"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."}}