{"id":"W3193591751","doi":"10.3390/s21175709","title":"Kinematic Zenith Tropospheric Delay Estimation with GNSS PPP in Mountainous Areas","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"GNSS positioning and interference","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada; University of Calgary","funders":"","keywords":"GNSS applications; Precise Point Positioning; Zenith; GLONASS; Ambiguity resolution; Global Positioning System; Remote sensing; Environmental science; Computer science; Meteorology; Geodesy; Troposphere; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003039668,0.0001072531,0.0001262021,0.00003367596,0.00002640429,0.00003843662,0.00004600399,0.00003945819,0.00006363009],"category_scores_gemma":[0.00002277707,0.00009810508,0.00001922932,0.0002306939,0.000017099,0.00006650032,0.000006780021,0.0001219982,0.00007692656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007724916,"about_ca_system_score_gemma":0.00001689852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004682603,"about_ca_topic_score_gemma":0.00008934329,"domain_scores_codex":[0.9994497,0.00002334904,0.0001399771,0.0001186829,0.0001018136,0.0001664272],"domain_scores_gemma":[0.9997283,0.00002705494,0.00001732983,0.0001475219,0.00004199961,0.00003776321],"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":[0.000007509885,0.0000271382,0.0007376971,0.0000761243,0.00001930328,0.000100465,0.0007753114,0.9959124,0.0008961796,0.0002563746,0.00008660361,0.001104851],"study_design_scores_gemma":[0.0003188391,0.00005673929,0.008015464,0.0002460172,0.00001720213,0.0002167945,0.0005047526,0.9846779,0.005526919,0.0001806795,0.0000437018,0.0001950686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809031,0.00008503305,0.009240079,0.00004375693,0.00007547332,0.00006131117,0.000001910908,0.000154557,0.009434774],"genre_scores_gemma":[0.9917293,0.000009163834,0.007893299,0.00002053945,0.00001593792,0.000008643388,0.00001718479,0.00002254193,0.0002833427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01123462,"threshold_uncertainty_score":0.4000609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005156779793212379,"score_gpt":0.1939856677406841,"score_spread":0.1888288879474717,"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."}}