{"id":"W4362672411","doi":"10.1016/j.applthermaleng.2023.120527","title":"Modeling of a new fuel cell based rail engine system using green fuel blends","year":2023,"lang":"en","type":"article","venue":"Applied Thermal Engineering","topic":"Advancements in Solid Oxide Fuel Cells","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; Research and Development; Transport Canada","keywords":"Environmental science; Exergy; Fossil fuel; Waste management; Greenhouse gas; Methane; Solid oxide fuel cell; Renewable energy; Engineering; Environmental engineering; Chemistry; Ecology","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":[0.0001391233,0.0005822551,0.0009870962,0.0003897953,0.0009152819,0.001096664,0.001266525,0.001844776,0.009080368],"category_scores_gemma":[0.0002701877,0.0004976447,0.0008450389,0.0004014971,0.0006762865,0.0008047632,0.0006326016,0.0006368154,0.0008160998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149102,"about_ca_system_score_gemma":0.001354177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05155995,"about_ca_topic_score_gemma":0.02903584,"domain_scores_codex":[0.9999071,0.00001545404,0.000003459491,0.00002156642,0.00002432375,0.00002809178],"domain_scores_gemma":[0.999897,0.00003595659,0.0000121327,0.000008528115,0.00002841393,0.00001798233],"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":[0.00004917867,0.00003268107,0.0004251798,0.00002832706,0.00001294784,0.0001330815,0.00002203628,0.9940403,0.002620807,0.001363295,0.000215609,0.001056422],"study_design_scores_gemma":[0.00001314585,0.00002377758,0.0001815994,0.00000277604,0.000006846813,0.000009945366,0.00001210356,0.9985079,0.0006237056,0.0001459914,0.0004673761,0.000004782317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8096631,0.0006034613,0.0879342,0.0007281486,0.0002319419,0.0001894984,0.001999452,0.001204375,0.09744579],"genre_scores_gemma":[0.9750209,0.0001884015,0.003551108,0.00006576201,0.0000152805,0.00008667135,0.0002578166,0.00008275666,0.02073136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05155995,"threshold_uncertainty_score":0.1025197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02038739344684479,"score_gpt":0.2256820650054909,"score_spread":0.2052946715586461,"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."}}