{"id":"W2050756646","doi":"10.1002/cjce.21656","title":"Efficient numerical integration of stiff differential equations in polymerisation reaction engineering: Computational aspects and applications","year":2012,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polymerization; Ordinary differential equation; Dimension (graph theory); Differential (mechanical device); Stiffness; Computer science; Differential equation; Stiff equation; Backward Euler method; Euler equations; Applied mathematics; Mathematics; Materials science; Thermodynamics; Physics; Mathematical analysis; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003077471,0.0001187066,0.000222125,0.0002714988,0.00004418094,0.00002469673,0.0001134289,0.00007260148,0.00001823441],"category_scores_gemma":[0.001080265,0.00009916189,0.00006773639,0.0002867678,0.00004695335,0.00008036746,0.00001232663,0.0003086051,8.369506e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001821805,"about_ca_system_score_gemma":0.0001123972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002543207,"about_ca_topic_score_gemma":0.00002415921,"domain_scores_codex":[0.9989556,0.00003847165,0.000496617,0.00007343619,0.0002221867,0.000213691],"domain_scores_gemma":[0.9985546,0.0007763805,0.0002122366,0.0001024729,0.0001040187,0.0002503183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003252437,0.0003002561,0.0005069682,0.000146893,0.0001460516,0.000001856564,0.003136823,0.102125,0.489129,0.3912503,0.00001703086,0.01320716],"study_design_scores_gemma":[0.0009617668,0.00006892965,0.01451514,0.0002563584,0.0002407995,0.000111392,0.0001196333,0.9049501,0.04609469,0.03215064,0.00009135271,0.0004391993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3915053,0.0000824948,0.6080269,0.0001171723,0.0001169644,0.0001246135,0.00000512195,0.000008453881,0.00001295382],"genre_scores_gemma":[0.977543,4.008323e-7,0.02223053,0.000005147899,0.0001793436,0.00001529693,0.000006646043,0.00001787061,0.000001763583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.802825,"threshold_uncertainty_score":0.4043705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880438923117374,"score_gpt":0.273974876192503,"score_spread":0.2451704869613293,"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."}}