{"id":"W2164769497","doi":"10.1109/icma.2005.1626777","title":"Navigation with IMU/GPS/digital compass with unscented Kalman filter","year":2006,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":164,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Inertial measurement unit; Global Positioning System; Compass; Kalman filter; Computer science; GPS/INS; Noise (video); Precision Lightweight GPS Receiver; Assisted GPS; Computer vision; Artificial intelligence; Geography; Telecommunications; Gps receiver","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":[0.00006575735,0.0001689826,0.0001376863,0.00005550098,0.0001402254,0.0004582356,0.0004504741,0.00004651825,0.00004158974],"category_scores_gemma":[0.000001841129,0.0001096261,0.0000271156,0.0003887655,0.00007390914,0.0008309637,0.00008424516,0.0001393898,0.00009809089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002077928,"about_ca_system_score_gemma":0.00002439413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000131095,"about_ca_topic_score_gemma":0.00005370887,"domain_scores_codex":[0.9987388,0.00002178418,0.0001871997,0.0004028325,0.0003531967,0.0002962206],"domain_scores_gemma":[0.9991358,0.0000575108,0.00007919285,0.0005424317,0.000108925,0.0000761329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004579037,0.00170288,0.1739126,0.00009604861,0.0001754194,0.0008102178,0.0008403944,0.05648031,0.0008018347,0.3756135,0.3354833,0.05362563],"study_design_scores_gemma":[0.008568401,0.001900577,0.1702,0.0008992832,0.00006237272,0.00146754,0.0003188958,0.6026171,0.00756506,0.006154043,0.1969428,0.00330385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1108271,0.00002003563,0.8677923,0.0007223972,0.0001479698,0.0001538649,0.00001520831,0.0006094912,0.01971157],"genre_scores_gemma":[0.9585857,6.79064e-7,0.03973155,0.0001998902,0.0001066627,0.000005349321,0.000192232,0.00001345931,0.00116451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8477585,"threshold_uncertainty_score":0.4470423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007463086523565589,"score_gpt":0.2006033444370807,"score_spread":0.1931402579135151,"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."}}