{"id":"W4404688488","doi":"10.1109/oceans55160.2024.10754101","title":"Ship Data Clustering for Improved Fuel Efficiency Optimization Decision Support Systems","year":2024,"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":"National Research Council Canada; Memorial University of Newfoundland","funders":"National Research Council Canada","keywords":"Cluster analysis; Computer science; Decision support system; Data mining; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001703204,0.001149147,0.001094176,0.002097426,0.0007880346,0.001032594,0.001463738,0.0007504634,0.001550123],"category_scores_gemma":[0.005591987,0.0004516945,0.000856167,0.002027218,0.000280238,0.001292616,0.001010749,0.001094106,0.000923804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040681,"about_ca_system_score_gemma":0.001260504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293722,"about_ca_topic_score_gemma":0.01191832,"domain_scores_codex":[0.9989299,0.0002613909,0.0001030671,0.0002996779,0.0003370333,0.00006888399],"domain_scores_gemma":[0.9981378,0.0006569984,0.0001525447,0.0002780074,0.0007236915,0.00005094294],"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":[0.0003052527,0.000294013,0.006607632,0.0001597136,0.0002149234,0.0001037364,0.0001924196,0.6272311,0.00835557,0.003206772,0.004624662,0.3487043],"study_design_scores_gemma":[0.00001279007,0.00003139093,0.001139382,0.000006905913,0.00001357655,0.0000119149,0.00005051041,0.9918191,0.003577855,0.002077844,0.001247916,0.00001084612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04775711,0.0002450464,0.9466131,0.0003410505,0.00007360013,0.0001982375,0.0006782658,0.002822642,0.001270881],"genre_scores_gemma":[0.4120125,0.000182814,0.5825662,0.0001477879,0.00006135393,0.0002383774,0.003184292,0.0002227642,0.001383835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01293722,"threshold_uncertainty_score":0.02572381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02627057881879937,"score_gpt":0.2720395396063908,"score_spread":0.2457689607875914,"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."}}