{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006796762,0.00005182704,0.00004351249,0.00005738725,0.0003087807,0.00002956297,0.00002713661,0.0000221451,0.00003032335],"category_scores_gemma":[0.000004669553,0.00006243862,0.00001445119,0.0001388375,0.000006595591,0.000118338,0.00001075155,0.00005911467,6.210651e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082295,"about_ca_system_score_gemma":0.000004345258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002383053,"about_ca_topic_score_gemma":0.00000731572,"domain_scores_codex":[0.9996738,0.00001155029,0.00009742911,0.00009480889,0.00005168671,0.00007066395],"domain_scores_gemma":[0.9998502,0.00002082672,0.00002004758,0.00005710682,0.0000350998,0.0000167084],"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":[0.00000481184,0.000007230635,0.00003901295,0.00001085718,0.000004768649,1.148914e-8,0.00007735655,0.9780627,0.01554111,0.0002529449,0.0001051737,0.005893954],"study_design_scores_gemma":[0.0001202521,0.00003697823,0.0001619187,0.000003234085,0.000008133339,0.000009681852,0.0002280087,0.9933879,0.003960055,0.0002156431,0.001794902,0.00007327163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1068651,0.00002392328,0.8915716,0.00001388193,0.0003189183,0.0002525802,0.000005906613,0.0001984895,0.0007495919],"genre_scores_gemma":[0.9734038,0.000005299211,0.02590821,0.00002425883,0.00004344876,0.000420338,0.00004478063,0.00001355628,0.0001363337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8665386,"threshold_uncertainty_score":0.2546173,"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."}}