{"id":"W2886930369","doi":"10.1109/euronav.2018.8433249","title":"Galileo E1/E5 Measurement Monitoring - Theory, Testing and Analysis","year":2018,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Multipath propagation; Galileo (satellite navigation); Metric (unit); Computer science; Multipath mitigation; Global Positioning System; Code (set theory); Real-time computing; Algorithm; Electronic engineering; Reliability engineering; Remote sensing; Engineering; Telecommunications","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":[0.000217612,0.00007509474,0.00008546269,0.0000777277,0.00007075896,0.00005635433,0.00005368567,0.00002350872,0.00004720982],"category_scores_gemma":[0.00006947402,0.00006677629,0.00002196714,0.0002273898,0.00002676534,0.00006089532,0.00001537933,0.00005277997,0.00003166678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003259397,"about_ca_system_score_gemma":0.00000312011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004179555,"about_ca_topic_score_gemma":0.00000761136,"domain_scores_codex":[0.9995388,0.00001357608,0.0000977727,0.0001029498,0.0001161765,0.0001306834],"domain_scores_gemma":[0.9996989,0.00003562851,0.000009822667,0.0001119449,0.0000996196,0.00004404351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001903676,0.00007867995,0.6351609,0.0001506961,0.002962274,0.000005805803,0.00297473,0.009352404,0.2351781,0.007060952,0.001934598,0.1051219],"study_design_scores_gemma":[0.0003466853,0.0002524901,0.4534677,0.0003196943,0.000780429,0.00001190675,0.0004459588,0.2321597,0.3080777,0.002813514,0.0005972622,0.0007268547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7230445,0.0002954793,0.1122767,0.00002029097,0.0003681606,0.00005495114,0.000001586958,0.0006042522,0.1633341],"genre_scores_gemma":[0.9956269,0.000004178451,0.004099762,0.000007354946,0.0001297752,0.000004502017,3.475177e-7,0.000008237821,0.0001189652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2725824,"threshold_uncertainty_score":0.2723058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04390026827820816,"score_gpt":0.236423746808523,"score_spread":0.1925234785303149,"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."}}