{"id":"W4403611275","doi":"10.24868/11158","title":"Optimizing Fuel Management for Halifax Class Frigates: Leveraging Sensor Data for Enhanced Efficiency","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Class (philosophy); Computer science; Environmental science; Fuel efficiency; Aeronautics; Automotive engineering; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004823111,0.0006660493,0.0005748417,0.0002949266,0.00006923446,0.0003100819,0.001413913,0.0003307617,0.00003679506],"category_scores_gemma":[0.000039921,0.0007163021,0.0002436936,0.0001569442,0.00002619019,0.0001006763,0.002132257,0.0006320357,0.0001044804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002903694,"about_ca_system_score_gemma":0.00002945389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008250045,"about_ca_topic_score_gemma":0.000006653999,"domain_scores_codex":[0.997285,0.00001173898,0.0005896727,0.001094583,0.0002485004,0.0007704984],"domain_scores_gemma":[0.9975557,0.0001691624,0.00006237813,0.002019095,0.00006345887,0.0001302012],"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":[0.00001330311,0.00002248185,6.52494e-8,0.01020646,0.000548629,0.000009006603,0.0004842904,0.9715642,0.003026724,0.001631388,0.008315285,0.004178153],"study_design_scores_gemma":[0.0004284226,0.00001861871,0.000001354566,0.0006556655,0.0002583676,0.000002717606,0.0001985667,0.9353512,0.003614844,0.001972446,0.05668409,0.0008136827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002775264,0.001336574,0.9622021,0.0002468027,0.004349144,0.002572457,0.000844967,0.003424657,0.02224804],"genre_scores_gemma":[0.4517104,0.0003618409,0.5409948,0.0001376757,0.0008499617,0.0007983978,0.001290322,0.0008526316,0.003003916],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4489352,"threshold_uncertainty_score":0.9995288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03208314710952946,"score_gpt":0.2604576376449527,"score_spread":0.2283744905354232,"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."}}