{"id":"W2772042746","doi":"10.1109/iros.2017.8206508","title":"Underwater acoustic-based navigation towards multi-vehicle operation and adaptive oceanographic sampling","year":2017,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Underwater glider; Dead reckoning; Underwater; Glider; Inertial measurement unit; Inertial navigation system; Global Positioning System; Computer science; Extended Kalman filter; Range (aeronautics); Sampling (signal processing); Marine engineering; Sea trial; Buoy; Kalman filter; Engineering; Filter (signal processing); Inertial frame of reference; Artificial intelligence; Computer vision; Geography; Telecommunications; Aerospace 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":[0.0002841362,0.0003318198,0.0003128791,0.0003871912,0.0002181507,0.000345349,0.0005421064,0.0002623356,0.000756368],"category_scores_gemma":[0.0007345162,0.0001394876,0.0001793877,0.0004250701,0.0002930371,0.0004968503,0.0009735219,0.0003081156,0.0003612225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002440636,"about_ca_system_score_gemma":0.000422324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004529939,"about_ca_topic_score_gemma":0.00407576,"domain_scores_codex":[0.9997509,0.00005381752,0.00001004703,0.0000530326,0.0001089513,0.00002326385],"domain_scores_gemma":[0.9997681,0.00003734848,0.00003176094,0.00003888245,0.0001113184,0.00001267078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001904837,0.00007973351,0.003840431,0.0001530212,0.00005055354,0.0001884509,0.0003664804,0.3774411,0.108567,0.01191555,0.002520373,0.4946869],"study_design_scores_gemma":[0.00001026229,0.00006863783,0.001851208,0.00001472426,0.00001094687,0.00006577548,0.00006907056,0.9793382,0.009611565,0.002896894,0.006048427,0.00001430447],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03741017,0.0003071828,0.9585331,0.00006883954,0.00005750931,0.00003032546,0.00003686596,0.0006348692,0.002921145],"genre_scores_gemma":[0.6435192,0.000326777,0.3518082,0.00006135889,0.00005364219,0.0001036663,0.0001681874,0.00007849075,0.003880453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004529939,"threshold_uncertainty_score":0.009007156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06350845716707844,"score_gpt":0.2782477932905252,"score_spread":0.2147393361234468,"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."}}