{"id":"W3037710185","doi":"10.1016/j.automatica.2021.109513","title":"A nonlinear navigation observer using IMU and generic position information","year":2021,"lang":"en","type":"preprint","venue":"Automatica","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University; Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inertial measurement unit; Observability; Global Positioning System; Observer (physics); Position (finance); Computer science; Inertial frame of reference; Control theory (sociology); Acceleration; Nonlinear system; Angular velocity; Accelerometer; Inertial navigation system; Computer vision; Artificial intelligence; Mathematics; Physics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008578293,0.0001910145,0.0002065,0.00008094311,0.0000649389,0.0002053767,0.00006107202,0.0002596798,0.00002284296],"category_scores_gemma":[0.00001797714,0.0002122746,0.00005843303,0.000134786,0.00001753137,0.0004823317,0.00008399366,0.0002552493,0.00001676968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001405516,"about_ca_system_score_gemma":0.00003272387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008050708,"about_ca_topic_score_gemma":0.000002874683,"domain_scores_codex":[0.9991294,0.0000312904,0.0003756261,0.0001254736,0.0001863611,0.0001518563],"domain_scores_gemma":[0.9995375,0.00001825638,0.000087842,0.0002014446,0.0001033399,0.00005156464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000244609,0.0001054264,0.0005019851,0.009050216,0.0004695459,0.00004845984,0.0101422,0.7703955,0.1294236,0.000381063,0.0004819018,0.0789757],"study_design_scores_gemma":[0.0001381626,0.000009375039,0.002631986,0.0003874288,0.00007358076,0.00002650816,0.0000622599,0.9880211,0.008160022,0.0001633096,0.00009032703,0.0002359245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808366,0.0002179394,0.01738263,0.00003630304,0.0005056396,0.0002560664,0.00002674762,0.0003902423,0.0003478537],"genre_scores_gemma":[0.9669626,0.00005910349,0.03115993,0.00005248442,0.0001579615,0.00001659686,0.001560536,0.00002721412,0.000003557841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2176256,"threshold_uncertainty_score":0.8656306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463650632968861,"score_gpt":0.2303338298903613,"score_spread":0.2156973235606727,"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."}}