{"id":"W2189520548","doi":"","title":"The Development of a Low-cost MEMS IMU/GPS Navigation System for Land Vehicles Using Auxiliary Velocity Updates in the Body Frame","year":2005,"lang":"en","type":"article","venue":"Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2005)","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inertial measurement unit; Microelectromechanical systems; Global Positioning System; Automotive industry; Computer science; Inertial navigation system; Engineering; Automotive engineering; Aerospace engineering; Telecommunications; Artificial intelligence; Inertial frame of reference","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":[0.0001503013,0.0003250374,0.0002840715,0.0002714588,0.0002569207,0.0002246437,0.0003494193,0.0004372865,0.001620663],"category_scores_gemma":[0.0001326415,0.0001331224,0.0002145649,0.000197142,0.0001338503,0.0002993782,0.000247573,0.0003380075,0.001199909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002221995,"about_ca_system_score_gemma":0.0004713682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001730969,"about_ca_topic_score_gemma":0.002547344,"domain_scores_codex":[0.9998701,0.00001473163,0.00000581223,0.00002216535,0.00007136267,0.00001572877],"domain_scores_gemma":[0.9999126,0.000006442299,0.00000807664,0.00000925828,0.00005320065,0.00001038662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001286752,0.00006603589,0.004862807,0.0002946869,0.00004878616,0.0005004711,0.000253409,0.00384441,0.586143,0.00572601,0.007357175,0.3907746],"study_design_scores_gemma":[0.00007895729,0.001694115,0.01610593,0.00008653373,0.0001916949,0.002210733,0.0001991725,0.08782218,0.6601945,0.001107821,0.2302068,0.000101595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1652194,0.002757325,0.8015789,0.0008470149,0.0007976047,0.0005985177,0.0005631676,0.004992618,0.02264538],"genre_scores_gemma":[0.5557258,0.001112736,0.4116135,0.0003773796,0.000167269,0.000305887,0.0005686337,0.0001066124,0.0300222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001730969,"threshold_uncertainty_score":0.005421638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153278306773541,"score_gpt":0.2646073137221509,"score_spread":0.2492794830447968,"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."}}