{"id":"W2088041466","doi":"10.1115/1.4000150","title":"A Method to Determine Fuel Transport Dynamics Model Parameters in Port Fuel Injected Gasoline Engines During Cold Start and Warm-Up Conditions","year":2010,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cold start (automotive); Inlet manifold; Automotive engineering; Fuel injection; Petrol engine; Air–fuel ratio; Gasoline; Nuclear engineering; Range (aeronautics); Fuel efficiency; Ignition system; Spark-ignition engine; Environmental science; Brake specific fuel consumption; Fuel tank; Vapor lock; Transient (computer programming); Engine efficiency; Coolant; Engineering; Mechanical engineering; Internal combustion engine; Combustion; Chemistry; Waste management; Combustion chamber; Computer science; 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":[0.0003073572,0.0007272502,0.0003881422,0.000450831,0.0002951768,0.0003144071,0.0003626737,0.0003933457,0.0006466953],"category_scores_gemma":[0.001133676,0.0003494519,0.0002625535,0.0002413764,0.0001599339,0.0005597523,0.0002724641,0.0005028151,0.000233227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003340546,"about_ca_system_score_gemma":0.0005541613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002439977,"about_ca_topic_score_gemma":0.002432154,"domain_scores_codex":[0.9998139,0.00002585495,0.00001025461,0.00004886076,0.00009210109,0.00000906167],"domain_scores_gemma":[0.9996399,0.0001390347,0.0000666923,0.00004922922,0.0000960566,0.000009096611],"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":[0.0003743118,0.0002226779,0.01385095,0.000368209,0.0001108632,0.0002104103,0.0004519192,0.1776608,0.5456586,0.00204852,0.0008252774,0.2582176],"study_design_scores_gemma":[0.00003368017,0.0003023884,0.007223257,0.00001353783,0.00004571665,0.0002081167,0.00005436592,0.8020846,0.1872156,0.0004857477,0.002288699,0.00004436756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08887887,0.00007412878,0.9082953,0.00003040574,0.00002216214,0.00009395892,0.0001464837,0.001591326,0.0008673792],"genre_scores_gemma":[0.7878868,0.0001108894,0.2097208,0.00001363605,0.000006114561,0.0002415174,0.0002916108,0.00009956478,0.001629095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002439977,"threshold_uncertainty_score":0.00485152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009619505189353087,"score_gpt":0.2514248412868897,"score_spread":0.2418053360975367,"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."}}