{"id":"W2115689645","doi":"10.1109/cca.2007.4389274","title":"Simulation of a Diesel Engine Aftertreatment System Using Singularly Perturbed Sliding Manifold","year":2007,"lang":"en","type":"article","venue":"The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Science Foundation Ireland","keywords":"Diesel particulate filter; Diesel engine; Soot; Diesel fuel; Control theory (sociology); Nonlinear system; Realization (probability); Manifold (fluid mechanics); Ordinary differential equation; Computer science; Invariant manifold; Inlet manifold; Automotive engineering; Differential equation; Mathematics; Engineering; Internal combustion engine; Mechanical engineering; Combustion; Mathematical analysis; Chemistry; Physics; Control (management); Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00137225,0.0009516419,0.001227328,0.0003817118,0.0009249031,0.0001755306,0.003986611,0.0004659535,0.000020117],"category_scores_gemma":[0.0003012,0.000589538,0.0006541011,0.001699424,0.0007247539,0.0003589004,0.0002393523,0.00105916,0.00002082687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006125467,"about_ca_system_score_gemma":0.0001538902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005342869,"about_ca_topic_score_gemma":0.00001332403,"domain_scores_codex":[0.9947402,0.00002818446,0.001931151,0.001053648,0.001319439,0.0009273484],"domain_scores_gemma":[0.990911,0.001482781,0.002678413,0.001312827,0.00343124,0.000183761],"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":[0.0005318438,0.0003953562,0.0002617249,0.0003858546,0.0004480546,1.82049e-7,0.000343111,0.07813206,0.6166337,0.2996525,0.0000880797,0.003127495],"study_design_scores_gemma":[0.003715029,0.0002718486,0.0006981705,0.001072907,0.001109088,0.00002236971,0.003384627,0.8627933,0.1159085,0.009112201,0.000966279,0.0009456895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1608347,0.0002973104,0.8122959,0.004872474,0.0004817373,0.01250164,0.0003987536,0.001124433,0.007193096],"genre_scores_gemma":[0.9956143,0.00002550752,0.00109062,0.000171471,0.0002855848,0.002185348,0.000003933481,0.0001223903,0.0005007951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8347796,"threshold_uncertainty_score":0.9996556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209854189896668,"score_gpt":0.2541932843863187,"score_spread":0.232094742487352,"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."}}