{"id":"W1994363759","doi":"10.4271/2014-01-2568","title":"Conditional Source-Term Estimation for the Numerical Simulation of Turbulent Combustion in Homogeneous-Charge SI Engines","year":2014,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Combustion; Homogeneous; Term (time); Turbulence; Computer science; Aerospace engineering; Mechanics; Environmental science; Statistical physics; Physics; Engineering; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004746157,0.00041861,0.0005301468,0.0001907069,0.0001743708,0.00004636439,0.0004137347,0.0004376069,0.000161536],"category_scores_gemma":[0.0006298735,0.0003492648,0.0002857744,0.0004229624,0.0003130007,0.0002137481,0.00007706472,0.0005569571,0.00002477624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002077309,"about_ca_system_score_gemma":0.00002380659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006175844,"about_ca_topic_score_gemma":0.001953177,"domain_scores_codex":[0.9977143,0.00007306886,0.0008561962,0.0004328827,0.0004854226,0.0004381178],"domain_scores_gemma":[0.997704,0.001341916,0.0001411509,0.0005802721,0.0001096172,0.0001229974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001505889,0.0001780652,0.00009984549,0.00009674186,0.00002843212,0.000001756257,0.0000311012,0.6393393,0.339002,0.01103503,0.0003531148,0.009683998],"study_design_scores_gemma":[0.001283314,0.0005957604,0.9339933,0.0001856834,0.00009983609,0.00003828739,0.00003066381,0.04896783,0.0001639954,0.00282983,0.01118978,0.0006217284],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9513219,0.0005108648,0.03174276,0.004329558,0.0008092221,0.003818213,0.0002299738,0.00425939,0.002978144],"genre_scores_gemma":[0.9967477,0.00008388983,0.002058967,0.0003185275,0.0001130233,0.0002885075,0.0002411802,0.00008262,0.00006562126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9338934,"threshold_uncertainty_score":0.9998959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008918191581562235,"score_gpt":0.2347400238455405,"score_spread":0.2258218322639783,"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."}}