{"id":"W2961411987","doi":"10.18280/i2m.180204","title":"A Navigation Accuracy Evaluation Method for Multi-path Platform Inertial Navigation System","year":2019,"lang":"fr","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inertial navigation system; Dead reckoning; Computer science; Path (computing); Navigation system; Inertial measurement unit; Computer vision; Real-time computing; Artificial intelligence; Inertial frame of reference; Geodesy; Global Positioning System; Geography; Telecommunications; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002883441,0.0005865296,0.0005918543,0.0002416429,0.0002782998,0.0002170597,0.0002732174,0.0007818829,0.0001909597],"category_scores_gemma":[0.0003142341,0.0006437379,0.0003131303,0.0005703285,0.00005688474,0.001749035,0.00004492106,0.0004958226,0.0004244758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042855,"about_ca_system_score_gemma":0.0002140405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006106079,"about_ca_topic_score_gemma":0.000024009,"domain_scores_codex":[0.9957694,0.0005303005,0.001282002,0.0007670661,0.0008888509,0.0007623102],"domain_scores_gemma":[0.9974481,0.0005259203,0.0006204044,0.000475529,0.000772449,0.0001575339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008085481,0.0002232049,0.00361429,0.003290492,0.0004851571,0.00001022101,0.003360677,0.2689874,0.1995089,0.01503179,0.0007926141,0.5038868],"study_design_scores_gemma":[0.006716502,0.0004368109,0.004838211,0.0006541045,0.0005553164,0.0000658866,0.001242534,0.9139746,0.06876204,0.0006997641,0.001419,0.0006352395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6964266,0.0008496196,0.2877725,0.0006229063,0.008685465,0.004432921,0.0002854403,0.000459572,0.0004649726],"genre_scores_gemma":[0.8640038,0.00003443524,0.1301525,0.00007252616,0.0008509036,0.0005862018,0.003900403,0.000106629,0.0002925853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6449872,"threshold_uncertainty_score":0.9996014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0561414932757676,"score_gpt":0.3615143093414422,"score_spread":0.3053728160656746,"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."}}