{"id":"W2610965671","doi":"","title":"Atmospheric Moisture Estimation Using GPS on a Moving Platform","year":2006,"lang":"en","type":"article","venue":"Proceedings of the 19th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2006)","topic":"GNSS positioning and interference","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Zenith; Remote sensing; Pseudorange; Precise Point Positioning; Environmental science; Ranging; Satellite; Meteorology; Geodesy; Computer science; Geography; Engineering; GNSS applications; Aerospace engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000492147,0.0002193684,0.0002902918,0.00005979495,0.0001532306,0.00003321561,0.001229515,0.0001540348,0.00000495211],"category_scores_gemma":[0.0004618766,0.0001378334,0.0003093784,0.0005434788,0.0003093837,0.0003321352,0.0003040545,0.0003530953,0.000001251711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764895,"about_ca_system_score_gemma":0.00002783769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001736954,"about_ca_topic_score_gemma":0.000003703565,"domain_scores_codex":[0.9977501,0.00001460469,0.0009732418,0.0002052747,0.000893894,0.0001628916],"domain_scores_gemma":[0.9980332,0.00008714878,0.001050347,0.0002710902,0.0005322325,0.00002597792],"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":[0.00007243806,0.0001782835,0.006045986,0.0003849251,0.00006406094,8.965696e-8,0.0001396871,0.4644508,0.5050411,0.01960555,0.0002871227,0.003729959],"study_design_scores_gemma":[0.0004418487,0.00007227829,0.03935831,0.008162528,0.00007665651,0.00001585155,0.00004311373,0.1242672,0.8154328,0.0114322,0.0004693096,0.000227867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873233,0.0001046542,0.0008053065,0.0003121472,0.001120096,0.0003445651,0.00003113543,0.00007088175,0.009887843],"genre_scores_gemma":[0.9928603,0.0000174348,0.006880375,0.00001833448,0.00006542836,0.000007277558,0.000007461102,0.00002433033,0.0001190472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3401836,"threshold_uncertainty_score":0.5620682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113428849686078,"score_gpt":0.2363497224429949,"score_spread":0.2250068374743871,"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."}}