{"id":"W4294316298","doi":"10.5957/imdc-2022-226","title":"A Decision Making Process for the Selection of Better Ship Main Dimensions with the Fuel EEDI Requirements","year":2022,"lang":"en","type":"article","venue":"","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Seakeeping; Naval architecture; Pareto principle; Hull; Multi-objective optimization; Engineering design process; Process (computing); Engineering; Fuel efficiency; Operations research; Selection (genetic algorithm); Shipbuilding; Computer science; Industrial engineering; Reliability engineering; Marine engineering; Automotive engineering; Operations management; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006640286,0.001417053,0.001046116,0.002000401,0.001229226,0.002908297,0.001316716,0.001518478,0.004919228],"category_scores_gemma":[0.007225044,0.0006259657,0.001170412,0.001059084,0.0009987521,0.001830534,0.001800872,0.001830749,0.001022239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188211,"about_ca_system_score_gemma":0.003935592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009733935,"about_ca_topic_score_gemma":0.001155723,"domain_scores_codex":[0.9954185,0.002023695,0.0003768331,0.0005807428,0.001311647,0.0002884759],"domain_scores_gemma":[0.9961874,0.002106939,0.0004468968,0.0002433402,0.0008183623,0.0001971772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006913492,0.0006157108,0.00374607,0.001266286,0.0001832753,0.0008358156,0.001824973,0.2949129,0.06068116,0.07257206,0.004279215,0.5583912],"study_design_scores_gemma":[0.0002516463,0.002237322,0.004937509,0.0007790425,0.0003496149,0.0007705493,0.002261896,0.783347,0.04377638,0.1121491,0.04884418,0.0002958683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02994301,0.0006397434,0.9597851,0.0005327124,0.00004827653,0.0005995081,0.00007751167,0.0001994919,0.008174693],"genre_scores_gemma":[0.2391317,0.0009049235,0.7558293,0.0002150456,0.00005965118,0.0005850258,0.000211388,0.00005945961,0.003003577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006640286,"threshold_uncertainty_score":0.03511763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950253007221875,"score_gpt":0.2680635480089686,"score_spread":0.2485610179367499,"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."}}