{"id":"W4402455216","doi":"10.11159/htff24.279","title":"Optimization of an Autonomous Underwater Vehicle Using a Gradient-Based Approach","year":2024,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Computer science; Underwater; Marine engineering; Geology; Engineering; Oceanography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000358706,0.0006162208,0.0006364623,0.0004768228,0.0002895026,0.0005812717,0.0005081373,0.0008034257,0.001481717],"category_scores_gemma":[0.0005016407,0.0003862099,0.000533778,0.0002575446,0.0004019076,0.0003125356,0.0005653288,0.0004028745,0.0002651729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003571174,"about_ca_system_score_gemma":0.001026027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004712517,"about_ca_topic_score_gemma":0.003083019,"domain_scores_codex":[0.9998583,0.00003379424,0.000005220752,0.00002334608,0.00005468789,0.00002466218],"domain_scores_gemma":[0.9998653,0.00005824963,0.0000157142,0.000007216742,0.00004281403,0.0000107149],"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":[0.00002805764,0.00002524512,0.0002905639,0.00004113557,0.00001917574,0.00004357504,0.00002164009,0.9794481,0.00399,0.002344251,0.0003124999,0.01343574],"study_design_scores_gemma":[0.000004191826,0.00002022496,0.00005992926,0.000002453783,0.000002477507,0.000005808485,0.000004515213,0.9988331,0.0003392715,0.0003472127,0.000378468,0.000002351477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0539785,0.0002710386,0.9369767,0.0001415503,0.0000694186,0.00008530218,0.00005999452,0.0004106835,0.008006879],"genre_scores_gemma":[0.7270548,0.0002059549,0.2652087,0.0001549939,0.00004356879,0.0003052784,0.0002029851,0.0001655027,0.006658311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004712517,"threshold_uncertainty_score":0.009370208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218434349380971,"score_gpt":0.2068139861305229,"score_spread":0.1946296426367132,"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."}}