{"id":"W2600460659","doi":"10.1109/cdc.2017.8264001","title":"Attitude and gyro bias estimation using GPS and IMU measurements","year":2017,"lang":"en","type":"article","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Western University","funders":"","keywords":"Global Positioning System; Inertial measurement unit; Control theory (sociology); Acceleration; Observer (physics); Exponential stability; Computer science; Inertial frame of reference; Attitude control; Stability (learning theory); Engineering; Artificial intelligence; Control engineering; Telecommunications; Physics; Nonlinear system","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":[0.00006783459,0.0000488304,0.0000487833,0.0000168578,0.0001331426,0.0000847733,0.00002395036,0.00002759788,0.000009079712],"category_scores_gemma":[0.00002876991,0.00004460681,0.000006034656,0.000009345265,0.00001510863,0.0001934578,0.00001157923,0.00002639678,0.000003353355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001436285,"about_ca_system_score_gemma":0.000001457698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001131281,"about_ca_topic_score_gemma":0.00002978292,"domain_scores_codex":[0.9997509,0.00000389574,0.00006102996,0.00005572366,0.0000640128,0.0000644762],"domain_scores_gemma":[0.9998548,0.000005325632,0.00001497035,0.00008311542,0.00001570689,0.00002610017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002514767,0.0000273596,0.1700847,0.0002940614,0.0001229165,0.0000064538,0.0006793085,0.05437328,0.6130158,0.0008205033,0.0005748103,0.1599756],"study_design_scores_gemma":[0.0003744819,0.00001046286,0.1495304,0.00003721294,0.00002208262,0.000006041783,0.000007667445,0.798544,0.05103321,0.000191447,0.0001108366,0.0001322282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888698,0.00006853203,0.007042661,0.00002638382,0.0001029309,0.00005413898,5.537356e-7,0.00005156346,0.003783397],"genre_scores_gemma":[0.9964588,0.00001131131,0.003448456,0.000009648708,0.00003261301,6.335916e-7,0.000001436548,0.000006728591,0.00003038952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7441707,"threshold_uncertainty_score":0.1819013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1214563233003975,"score_gpt":0.3022467059327056,"score_spread":0.1807903826323081,"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."}}