{"id":"W1970594122","doi":"10.1109/icif.2005.1591871","title":"Comparison of forward Vs. feedback Kalman filter for aided inertial navigation system","year":2005,"lang":"en","type":"article","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Kalman filter; Inertial navigation system; Gyroscope; Inertial measurement unit; Computer science; Accelerometer; GPS/INS; Global Positioning System; Control theory (sociology); Inertial frame of reference; Control engineering; Engineering; Artificial intelligence; Aerospace engineering; Assisted GPS; Control (management); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002316758,0.0007096005,0.0008189298,0.0007191515,0.0005373737,0.0008427262,0.0005603782,0.001404123,0.005599037],"category_scores_gemma":[0.007386287,0.000275155,0.0005265004,0.0003158477,0.0002555943,0.001422912,0.0004416835,0.0004490943,0.001111257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007459067,"about_ca_system_score_gemma":0.0009664726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01436774,"about_ca_topic_score_gemma":0.01106728,"domain_scores_codex":[0.9985332,0.0004013411,0.00009082985,0.0002060215,0.0006114937,0.0001570266],"domain_scores_gemma":[0.9960715,0.001921294,0.00007986639,0.0002070561,0.001681719,0.00003852327],"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":[0.003589855,0.0001546221,0.005536384,0.0007643419,0.0003357652,0.0001760273,0.0003314606,0.2184256,0.02129954,0.010686,0.004346462,0.734354],"study_design_scores_gemma":[0.000306022,0.0008820737,0.008631134,0.00008081485,0.0002470252,0.000256247,0.0001240332,0.9539698,0.02202305,0.003033322,0.01036634,0.00008015254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06332922,0.002559605,0.9212177,0.0002911255,0.0003965251,0.0001129436,0.0001871063,0.002661479,0.009244206],"genre_scores_gemma":[0.8436968,0.001396778,0.1441234,0.0001873603,0.0001641659,0.000183293,0.0005548996,0.0001734283,0.009519844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01436774,"threshold_uncertainty_score":0.02856821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635492937691326,"score_gpt":0.2699677625047436,"score_spread":0.2536128331278303,"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."}}