{"id":"W82572485","doi":"10.1007/978-1-4614-8453-0_13","title":"Numerical Methods for ODEs","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Runge–Kutta methods; Residual; Ode; Sketch; Applied mathematics; Linear multistep method; Stability (learning theory); Mathematics; Continuation; Computer science; Numerical methods for ordinary differential equations; Calculus (dental); Algorithm; Ordinary differential equation; Numerical analysis; Differential equation; Mathematical analysis; Collocation method; Differential algebraic 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":[0.0006290415,0.001677374,0.001313103,0.001685905,0.0006077494,0.001669144,0.001270932,0.001316903,0.03119375],"category_scores_gemma":[0.001814125,0.0005434008,0.0009879312,0.001405884,0.001417497,0.00223136,0.001620658,0.00340157,0.0194079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009645319,"about_ca_system_score_gemma":0.0008495026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009739269,"about_ca_topic_score_gemma":0.001504583,"domain_scores_codex":[0.9993962,0.0001121145,0.00003599404,0.00007884354,0.0003479072,0.00002891334],"domain_scores_gemma":[0.9995615,0.0001878336,0.00001749846,0.00007715692,0.000137958,0.00001805464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000126156,0.00002980294,0.00007097588,0.0005805971,0.00003260968,0.00004412897,0.0001651416,0.005561056,0.002215193,0.6554789,0.1129788,0.2228302],"study_design_scores_gemma":[0.00001356505,0.00001393825,0.0001430018,0.0002482735,0.00001374038,0.0001135376,0.00002494648,0.01651928,0.001130567,0.4023237,0.5794293,0.00002613232],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009410394,0.04713118,0.6798572,0.001675099,0.005526466,0.0001024097,0.000506868,0.002262063,0.2619977],"genre_scores_gemma":[0.02979559,0.05196279,0.4553756,0.001652192,0.00433377,0.0006283786,0.0017596,0.003350621,0.4511416],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03119375,"threshold_uncertainty_score":0.1043535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2051165998989182,"score_gpt":0.4696039136032286,"score_spread":0.2644873137043104,"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."}}