{"id":"W2028317614","doi":"10.1243/09544070jauto539","title":"Natural gas spark ignition engine efficiency and NO <i> <sub>x</sub> </i> emission improvement using extreme exhaust gas recirculation enabled by partial reforming","year":2008,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Exhaust gas recirculation; Combustion; Gas engine; Diesel fuel; Thermal efficiency; Ignition system; Natural gas; Spark-ignition engine; Materials science; Exhaust gas; Dilution; Environmental science; Waste management; Chemistry; Automotive engineering; Thermodynamics; Engineering; Physics","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":[0.0002091653,0.0002969503,0.0002281205,0.0001514296,0.00008979101,0.0002978875,0.0002976138,0.0001879063,0.0006576411],"category_scores_gemma":[0.0001659658,0.0001318349,0.0002420214,0.0001507156,0.0001787556,0.0003555164,0.0001750961,0.0002154262,0.0002744466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000206259,"about_ca_system_score_gemma":0.0001183511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006757666,"about_ca_topic_score_gemma":0.001302216,"domain_scores_codex":[0.9998704,0.00001234361,0.000009272009,0.0000274411,0.00004956528,0.00003092123],"domain_scores_gemma":[0.9999204,0.00001372439,0.00002279098,0.000007843999,0.00002769651,0.000007691168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003829935,0.00007033718,0.001613878,0.00005395207,0.0000127689,0.00002933483,0.00002096282,0.000901248,0.9890249,0.0001047557,0.00007341212,0.007711511],"study_design_scores_gemma":[0.00000708676,0.0002525802,0.005982735,0.000001582226,0.00001255145,0.0000255151,0.00001077493,0.002610959,0.9906772,0.00001038527,0.0004047841,0.00000379144],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971278,0.0002109945,0.00147369,0.00001295502,0.000003735292,0.000003926438,0.00003735166,0.00006140114,0.001068127],"genre_scores_gemma":[0.9978346,0.0001443171,0.001122556,0.000009414492,0.000002118601,0.000003819786,0.00009264367,0.0000166819,0.0007737214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006757666,"threshold_uncertainty_score":0.002200067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123894908845654,"score_gpt":0.2015606222697439,"score_spread":0.1891711313851785,"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."}}