{"id":"W4387408019","doi":"10.1016/j.energy.2023.129276","title":"Exergoeconomic and exergoenvironmental analyses of a potential marine engine powered by eco-friendly fuel blends with hydrogen","year":2023,"lang":"en","type":"article","venue":"Energy","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":15,"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":"Diesel engine; Environmental science; Methane; Waste management; Hydrogen; Methanol; Diesel fuel; Biofuel; Fossil fuel; Pulp and paper industry; Process engineering; Engineering; Chemistry; Automotive engineering; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005294118,0.0001993931,0.0003136238,0.0001340067,0.0000338827,0.00001391173,0.0001241925,0.00006440266,0.0002011891],"category_scores_gemma":[0.000001147343,0.0001786219,0.00007753243,0.000148481,0.00005958043,0.00007138363,0.00005664907,0.00005391741,0.00001497289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002990511,"about_ca_system_score_gemma":0.000009573375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005250177,"about_ca_topic_score_gemma":0.00005703984,"domain_scores_codex":[0.9991438,0.00001302761,0.000255381,0.0002109822,0.0001157079,0.0002611358],"domain_scores_gemma":[0.9996305,0.0000135951,0.00004733484,0.0002063198,0.000006477893,0.00009577605],"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":[0.0003145493,0.0001380685,0.001300361,0.0003246479,0.002612829,0.000127187,0.0007847436,0.609307,0.3484868,0.001291351,0.006866807,0.02844574],"study_design_scores_gemma":[0.004926446,0.0008353578,0.00694385,0.0001416829,0.0008373749,0.0001783941,0.00216489,0.8475997,0.1113852,0.001131242,0.02160203,0.002253891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896107,0.001422973,0.005265732,0.00001696546,0.0001474789,0.00003830175,0.00005834811,0.0001987989,0.003240682],"genre_scores_gemma":[0.9971529,0.0009773667,0.00008204359,0.0000071127,0.00005343388,0.00001263815,0.000163657,0.00004554643,0.001505287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2382927,"threshold_uncertainty_score":0.728399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003584716952031951,"score_gpt":0.1884364871546292,"score_spread":0.1848517702025973,"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."}}