{"id":"W2289110623","doi":"10.23919/oceans.2015.7404407","title":"Autonomous shallow water bathymetric measurements for environmental assessment and safe navigation using USVs","year":2015,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Sonar; Hydrography; Marine engineering; Remotely operated underwater vehicle; Unmanned surface vehicle; Underwater; Echo sounding; Hydrographic survey; Hull; Remote sensing; Computer science; Side-scan sonar; Systems engineering; Oceanography; Environmental science; Engineering; Geology; Mobile robot; Robot; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000265774,0.00024919,0.0002250453,0.0004536877,0.0003404962,0.0006009804,0.0003566397,0.0002514647,0.0007374862],"category_scores_gemma":[0.0005542921,0.0001480687,0.0001423409,0.0005086098,0.0003661144,0.0008880951,0.000661741,0.0002714875,0.0002886653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007264937,"about_ca_system_score_gemma":0.001324618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03096778,"about_ca_topic_score_gemma":0.06036892,"domain_scores_codex":[0.9997178,0.00006240794,0.000008376729,0.0000263613,0.0001587331,0.00002635311],"domain_scores_gemma":[0.9997192,0.00003712567,0.00002205141,0.00003682309,0.0001619147,0.00002280213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002086908,0.00006937964,0.01984002,0.0001639317,0.00004574288,0.0002408501,0.0006901606,0.09726895,0.1393175,0.01189645,0.00587748,0.7243808],"study_design_scores_gemma":[0.00007516847,0.0005306847,0.04044768,0.0001291488,0.00006865805,0.0003624173,0.002378284,0.7457413,0.1181092,0.01090497,0.08112809,0.0001243642],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4224289,0.001573301,0.5439048,0.001114006,0.0001649874,0.0001429775,0.0004667424,0.002210024,0.02799427],"genre_scores_gemma":[0.8966531,0.0004855014,0.09871624,0.00008248531,0.0000141458,0.00004020649,0.0001994486,0.00006715703,0.003741641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03096778,"threshold_uncertainty_score":0.06157506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1091814606548942,"score_gpt":0.2849175739262883,"score_spread":0.1757361132713941,"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."}}