{"id":"W2023478049","doi":"10.1115/ices2006-1377","title":"Modeling the Performance of a Turbo-Charged S.I. Natural Gas Engine With Cooled EGR","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; National Research Council Canada","funders":"","keywords":"Turbocharger; Gas engine; Exhaust gas recirculation; Natural gas; Turbo; Ignition system; Automotive engineering; Range (aeronautics); Environmental science; Computer science; Gas compressor; Nuclear engineering; Engineering; Mechanical engineering; Internal combustion engine; Waste management; Aerospace engineering","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":[0.0002385192,0.0007557912,0.0005977266,0.0002728998,0.000320228,0.0006103997,0.001104528,0.001247692,0.0009103575],"category_scores_gemma":[0.0004456961,0.0003507279,0.0008463984,0.0002893495,0.0004039018,0.000498049,0.0002605201,0.0005049055,0.0002572082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007760234,"about_ca_system_score_gemma":0.001131597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02840894,"about_ca_topic_score_gemma":0.0113348,"domain_scores_codex":[0.9999086,0.00001570984,0.000004548233,0.00001691428,0.00003099141,0.00002326492],"domain_scores_gemma":[0.999871,0.00005224676,0.00002283574,0.00000922123,0.00003416155,0.00001036661],"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":[0.00004462899,0.00001705122,0.0004147312,0.00002134907,0.000005252507,0.0000291837,0.000009670925,0.9956133,0.00284525,0.0002638008,0.00004302025,0.0006928251],"study_design_scores_gemma":[0.000005057566,0.00004412472,0.0002761437,0.000002209906,0.000004497593,0.000004988586,0.000005435407,0.997999,0.001509303,0.00007532859,0.00006904759,0.000004778157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9382139,0.0002861826,0.04516121,0.0001906134,0.0000409828,0.0001062965,0.0005783845,0.0002016176,0.01522077],"genre_scores_gemma":[0.9949847,0.0001338429,0.001928327,0.00001460374,0.000003675421,0.00004352523,0.0001433054,0.00001072508,0.002737161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02840894,"threshold_uncertainty_score":0.05648714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004814453906040234,"score_gpt":0.1860762436169434,"score_spread":0.1812617897109031,"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."}}