{"id":"W3043989219","doi":"10.1007/s00190-020-01390-8","title":"Raytracing atmospheric delays in ground-based GNSS reflectometry","year":2020,"lang":"en","type":"article","venue":"Journal of Geodesy","topic":"GNSS positioning and interference","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Mitacs; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Zenith; GNSS applications; Geodesy; Altimeter; Atmospheric refraction; Remote sensing; Atmospheric correction; Elevation (ballistics); Reflectometry; Satellite; Physics; Geology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005599588,0.0006802995,0.0003802293,0.001113726,0.000332371,0.0009372731,0.0006844449,0.0004543164,0.001282498],"category_scores_gemma":[0.003891383,0.000487413,0.0003703444,0.002545192,0.0004404066,0.001093845,0.0007501456,0.0008498863,0.0008417219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005995347,"about_ca_system_score_gemma":0.001229156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00913093,"about_ca_topic_score_gemma":0.0152949,"domain_scores_codex":[0.9995742,0.0000873481,0.00001846999,0.00007781202,0.0001826774,0.00005949327],"domain_scores_gemma":[0.9993846,0.0002573989,0.00007406071,0.0001136508,0.0001442231,0.00002587909],"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":[0.0005473008,0.0001197796,0.01560164,0.0002358163,0.0001415159,0.0002737918,0.0003444729,0.5483148,0.0796354,0.01584105,0.001586907,0.3373575],"study_design_scores_gemma":[0.00007544533,0.0001527594,0.02098721,0.00006584218,0.0001233342,0.0003559185,0.0001622848,0.9166076,0.04504866,0.006516245,0.009807137,0.00009754222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2775633,0.001205871,0.7122479,0.0001480105,0.0003572386,0.0000800136,0.0007693296,0.001704173,0.005924201],"genre_scores_gemma":[0.7304994,0.001470357,0.2613358,0.00006065727,0.0001790112,0.00006338975,0.0008785613,0.00052544,0.004987374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00913093,"threshold_uncertainty_score":0.01815557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703912700695977,"score_gpt":0.2309609591988105,"score_spread":0.2139218321918508,"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."}}