{"id":"W2558099083","doi":"10.3390/s16122017","title":"MEMS IMU Error Mitigation Using Rotation Modulation Technique","year":2016,"lang":"en","type":"article","venue":"Sensors","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Inertial measurement unit; GNSS applications; Inertial navigation system; Rotation (mathematics); Units of measurement; Inertial reference unit; Global Positioning System; Computer science; Microelectromechanical systems; Accelerometer; Inertial frame of reference; Engineering; Artificial intelligence; Telecommunications; Physics","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":[0.00008680092,0.0001025207,0.00008168976,0.00008989892,0.00005337158,0.00001309123,0.00003441395,0.00009807653,0.0000322738],"category_scores_gemma":[0.00002889229,0.00008384045,0.0000373728,0.0001505122,0.00001857887,0.000192675,0.000004224074,0.00004957394,0.00004485368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351895,"about_ca_system_score_gemma":0.00000504392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003179904,"about_ca_topic_score_gemma":0.000007440143,"domain_scores_codex":[0.9993981,0.00002249265,0.0001815836,0.0001167253,0.0001314375,0.0001497159],"domain_scores_gemma":[0.9997267,0.00002578,0.00003521549,0.0001149307,0.00006080888,0.00003656824],"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":[0.000005153053,0.000003141025,0.0003109534,0.00001126065,0.000006000445,9.668842e-7,0.00008949596,0.08073189,0.9101881,0.0001358846,0.00002616033,0.008491033],"study_design_scores_gemma":[0.0002057976,0.00001312277,0.004709629,0.00006271895,0.00001033814,0.000007367119,0.00002348111,0.3252905,0.6684312,0.0008872235,0.000189029,0.000169532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9307242,0.000009333456,0.06768721,0.00006090763,0.0002353224,0.0002455273,0.000005960109,0.0003370787,0.000694473],"genre_scores_gemma":[0.9972516,0.000006103383,0.002436113,0.000008469218,0.0001652596,0.0000119922,0.0000154974,0.00003047184,0.0000745386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2445586,"threshold_uncertainty_score":0.3418914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135572866483457,"score_gpt":0.2412883944385574,"score_spread":0.2277311077902117,"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."}}