{"id":"W2058804260","doi":"10.1016/j.ijhydene.2011.04.185","title":"Utilization of hydrogen produced from urea on board to improve performance of vehicles","year":2011,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Urea; Ammonia; Diesel fuel; NOx; Hydrogen; Selective catalytic reduction; Diesel exhaust fluid; Gasoline; Diesel engine; Chemistry; Hydrogen vehicle; Environmental science; Catalysis; Carbon dioxide; Pulp and paper industry; Waste management; Hydrogen fuel; Diesel exhaust; Automotive engineering; Organic chemistry; Engineering; Combustion","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009737784,0.0002277693,0.000247628,0.0001890534,0.0001851546,0.0003278524,0.0003323523,0.0002301775,0.0006566115],"category_scores_gemma":[0.000113445,0.0001145381,0.0001822823,0.0001436929,0.0001048317,0.0003375039,0.0001854196,0.0002621878,0.0001258898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001745264,"about_ca_system_score_gemma":0.0002163835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009715118,"about_ca_topic_score_gemma":0.002323203,"domain_scores_codex":[0.999948,0.000004999815,0.000002986121,0.00001139656,0.00001524708,0.00001728036],"domain_scores_gemma":[0.9999574,0.000004935753,0.0000090781,0.000003465811,0.0000138862,0.0000112995],"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":[0.0001503996,0.0001015059,0.0004118247,0.00006214973,0.000008874077,0.00004396417,0.00001422956,0.0003420254,0.9918334,0.00006919967,0.00005383265,0.006908536],"study_design_scores_gemma":[0.000007830046,0.0003564919,0.000717132,0.000004523139,0.00001654055,0.00002076402,0.00002128908,0.001711675,0.9964135,0.0000125821,0.0007147283,0.000002921617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970762,0.0006579258,0.001426972,0.00002470567,0.00004461373,0.000009406384,0.00003126364,0.00004086984,0.0006881678],"genre_scores_gemma":[0.9973083,0.0003320365,0.001335578,0.00001116069,0.000006794946,0.000004580827,0.00004724798,0.00001095598,0.000943505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009715118,"threshold_uncertainty_score":0.00219655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02101262451040482,"score_gpt":0.2433328689967614,"score_spread":0.2223202444863566,"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."}}