{"id":"W2964649202","doi":"10.1016/j.combustflame.2019.07.032","title":"A new methodology to calculate process rates in a kinetic Monte Carlo model of PAH growth","year":2019,"lang":"en","type":"article","venue":"Combustion and Flame","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Horizon 2020; National Research Council of Science and Technology; Cambridge Commonwealth Trust; Consejo Nacional de Ciencia y Tecnología; National Research Foundation; European Commission","keywords":"Monte Carlo method; Kinetic Monte Carlo; Chemistry; Kinetic energy; Equivalence ratio; Equivalence (formal languages); Thermodynamics; Statistical physics; Growth rate; Combustion; Physical chemistry; Physics; Mathematics","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":[0.001455071,0.0009700712,0.0009397402,0.001061677,0.001056685,0.001086318,0.002608552,0.001791185,0.003520322],"category_scores_gemma":[0.003578731,0.0008319907,0.001287513,0.00106257,0.0006418289,0.001618409,0.0008543382,0.002152167,0.0009917656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227778,"about_ca_system_score_gemma":0.001637727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006892288,"about_ca_topic_score_gemma":0.006592454,"domain_scores_codex":[0.9995322,0.0001147014,0.00002832118,0.00004803827,0.0002391577,0.00003752591],"domain_scores_gemma":[0.9986191,0.0007368387,0.00009709121,0.0001640484,0.0003089643,0.00007398958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003106517,0.0001169751,0.0005756413,0.0001051003,0.00007056911,0.00009425664,0.00005377828,0.8971332,0.007386427,0.07296277,0.001037455,0.02043271],"study_design_scores_gemma":[0.000006957803,0.000007489362,0.00004480195,0.00000432045,0.000009894636,0.00002056549,0.000002306977,0.9946755,0.0009527811,0.003196591,0.001071376,0.000007419721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004378704,0.000128149,0.9916804,0.00008632695,0.00009977914,0.00008146346,0.00006872392,0.0003130611,0.003163365],"genre_scores_gemma":[0.2503712,0.0007250091,0.7311741,0.0003392855,0.0002680988,0.0009819777,0.000355275,0.001200192,0.01458485],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006892288,"threshold_uncertainty_score":0.01370436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0330814712524115,"score_gpt":0.2925800417466491,"score_spread":0.2594985704942376,"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."}}