{"id":"W2133272479","doi":"10.1109/taes.2012.6324671","title":"Integration of a Triaxial Magnetometer into a Helicopter UAV GPS-Aided INS","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Else Kröner-Fresenius-Stiftung","keywords":"Observability; Heading (navigation); Global Positioning System; Extended Kalman filter; Inertial navigation system; Kalman filter; Magnetometer; Compass; Inertial measurement unit; Computer science; GPS/INS; Control theory (sociology); Engineering; Inertial frame of reference; Aerospace engineering; Assisted GPS; Computer vision; Artificial intelligence; Geography; Physics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001814089,0.0001623219,0.0002209073,0.0001400383,0.00006805723,0.00002620019,0.0000467661,0.0001283272,0.00002279578],"category_scores_gemma":[0.000002523976,0.0001462676,0.00007313336,0.0002319869,0.00002679364,0.0001947272,3.855941e-7,0.0002227705,0.00002497305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001481623,"about_ca_system_score_gemma":0.00001426253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003657932,"about_ca_topic_score_gemma":0.0001719689,"domain_scores_codex":[0.9990855,0.00004931127,0.0002561336,0.0001171101,0.0001477692,0.0003441564],"domain_scores_gemma":[0.9996647,0.00004190217,0.00003982414,0.0001409913,0.00003653212,0.00007610969],"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":[0.0002022255,0.0001300249,0.00005496582,0.000200657,0.0001465697,3.920886e-7,0.003242679,0.01151893,0.9628472,0.0005362973,0.0002043219,0.02091568],"study_design_scores_gemma":[0.002857235,0.001176208,0.0005327032,0.0002700894,0.0002362416,0.00006390488,0.0008317302,0.05853358,0.9302843,0.00005702619,0.004409695,0.000747338],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8025174,0.0009146639,0.1950346,0.00003176076,0.0008399298,0.0002865675,0.000006005117,0.0001001542,0.000268905],"genre_scores_gemma":[0.9991143,0.000267709,0.00006934305,0.00001357164,0.0001611455,0.00006151787,0.000003841174,0.00002724849,0.0002813584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1965969,"threshold_uncertainty_score":0.596462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009503820701856885,"score_gpt":0.2226815022875951,"score_spread":0.2131776815857382,"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."}}