{"id":"W3044544879","doi":"10.1016/j.enconman.2020.113166","title":"Sustainable energy design of cruise ships through dynamic simulations: Multi-objective optimization for waste heat recovery","year":2020,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"TRNSYS; Cruise; Engineering; Energy consumption; Payback period; Liquefied natural gas; Waste heat; Waste heat recovery unit; Marine engineering; Automotive engineering; Energy (signal processing); Natural gas; Waste management; Mechanical engineering; Heat exchanger; Production (economics)","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":[],"consensus_categories":[],"category_scores_codex":[0.00008426335,0.0001202291,0.000131644,0.00003824209,0.000181265,0.00001494898,0.0001015007,0.00004612376,0.0008553122],"category_scores_gemma":[0.00001127148,0.0001141555,0.00004177958,0.0002342647,0.00006154234,0.0002163158,0.0001164529,0.00002445959,0.000001676675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007084887,"about_ca_system_score_gemma":0.000008314835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004999405,"about_ca_topic_score_gemma":0.00001234942,"domain_scores_codex":[0.9991415,0.00003363446,0.000184752,0.0003090218,0.0001382933,0.0001928513],"domain_scores_gemma":[0.9996853,0.00004628569,0.00005123049,0.0001161509,0.00001891815,0.00008212333],"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":[0.0001404493,0.00008524382,0.00003227433,0.00007725776,0.00002011044,0.000005598008,0.0002237687,0.991958,0.0003029856,0.002430206,0.001182297,0.003541769],"study_design_scores_gemma":[0.0009354936,0.0001714078,0.00003806699,0.00001723918,0.00004149864,2.322328e-7,0.001136553,0.9667462,0.001079765,0.0002266869,0.02946087,0.0001460021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001270548,0.0001103494,0.9959556,0.0004235242,0.00004340607,0.0002875587,0.000006358889,0.0000282953,0.001874355],"genre_scores_gemma":[0.9572626,0.001342902,0.03380892,0.0008157091,0.0000100607,0.00004217045,0.00006813467,0.00001807021,0.006631403],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9621467,"threshold_uncertainty_score":0.9365069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465377391584037,"score_gpt":0.2160461285674315,"score_spread":0.2013923546515911,"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."}}