{"id":"W4308213857","doi":"10.1109/wisee49342.2022.9926799","title":"Fault Detection and Correction Using Observation Domain Optimization for GNSS Applications","year":2022,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; GNSS applications; Receiver autonomous integrity monitoring; Real-time computing; Scalability; Fault detection and isolation; Unavailability; Global Positioning System; Data mining; Artificial intelligence; Reliability engineering; Engineering","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":[0.000346133,0.0006795886,0.0006252049,0.0004340583,0.0002243028,0.0003579071,0.0004293043,0.0004835568,0.001299328],"category_scores_gemma":[0.001324958,0.0002129574,0.0004103315,0.0004912962,0.00030662,0.0004388867,0.000400634,0.0007079469,0.0003942483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003267035,"about_ca_system_score_gemma":0.0009318672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007545598,"about_ca_topic_score_gemma":0.006083167,"domain_scores_codex":[0.9998294,0.00003676953,0.000009433996,0.00003793335,0.00006502588,0.00002135253],"domain_scores_gemma":[0.9996475,0.000149005,0.00006224112,0.00003305547,0.00009432455,0.00001382435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007309802,0.00004354022,0.0009108711,0.00004928863,0.00003172065,0.00003382757,0.00002323769,0.8531368,0.005081015,0.001235472,0.001128381,0.1382528],"study_design_scores_gemma":[0.000003184776,0.000009363624,0.0001617086,0.000001807415,0.000001899866,0.000005654319,0.000002983631,0.998579,0.0006617031,0.0003284769,0.0002423544,0.000001801471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01282308,0.0001779507,0.9858417,0.00006348739,0.00002313595,0.00001994148,0.00003269241,0.0005035441,0.0005144146],"genre_scores_gemma":[0.4897444,0.000287542,0.5070567,0.000097187,0.00006591177,0.0001070816,0.0003632109,0.0001377955,0.00214015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007545598,"threshold_uncertainty_score":0.01500332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176290871975544,"score_gpt":0.2230938424486226,"score_spread":0.2054647552510682,"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."}}