{"id":"W1908200177","doi":"10.1109/mwscas.2004.1354381","title":"DGPS aided INS navigation for AUV","year":2004,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Inertial navigation system; Computer science; Global Positioning System; Heading (navigation); Positioning system; Differential GPS; Acceleration; Marine engineering; Real-time computing; Geodesy; Inertial frame of reference; Engineering; Geology; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000184784,0.00003581695,0.00003209009,0.00001437403,0.00002232431,0.00001508831,0.00003094121,0.00002288122,0.00001706673],"category_scores_gemma":[0.000005464488,0.00003418672,0.00001666322,0.00002882197,0.000004701354,0.00006518626,0.000002478625,0.00002992604,0.00006086313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002989114,"about_ca_system_score_gemma":0.000004116478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001777464,"about_ca_topic_score_gemma":0.000004422661,"domain_scores_codex":[0.9998069,0.000001037758,0.00005556696,0.00004248328,0.00002546749,0.00006851802],"domain_scores_gemma":[0.9999063,0.000007791666,0.000003776848,0.00004861461,0.00001602188,0.00001750301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001539631,0.00005240989,0.0001399206,0.0002044905,0.00006256248,0.000001637089,0.001957762,0.4641725,0.1773243,0.3350708,0.01213607,0.008862197],"study_design_scores_gemma":[0.001391404,0.0002321777,0.002123325,0.0002549917,0.00001711756,0.00001585007,0.0001556298,0.09539118,0.8695264,0.02500104,0.005496222,0.0003946366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5754328,0.00001806212,0.3935594,0.0001013782,0.0002258101,0.00008196152,0.00000390483,0.000382598,0.0301941],"genre_scores_gemma":[0.9945061,0.00000159471,0.004978185,0.00003522381,0.00003479385,0.0000168015,0.0000171396,0.000007054283,0.0004031505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6922022,"threshold_uncertainty_score":0.1394094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030818473396807,"score_gpt":0.2183428442095225,"score_spread":0.2080346594755544,"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."}}