{"id":"W2188345117","doi":"","title":"4-D TROPOSPHERE MODELING USING A REGIONAL GPS NETWORK IN SOUTHERN ALBERTA","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003)","topic":"GNSS positioning and interference","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Troposphere; Global Positioning System; Hydrostatic equilibrium; Water vapor; Ranging; Environmental science; Atmosphere (unit); Meteorology; Atmospheric model; Remote sensing; Range (aeronautics); Geodesy; Component (thermodynamics); Geology; Geography; Computer science; Aerospace engineering; Physics; Telecommunications; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001159822,0.0003781644,0.0002218172,0.0005501274,0.0008029389,0.0008482246,0.001098423,0.0004368232,0.002099161],"category_scores_gemma":[0.0003970357,0.0002997503,0.0003298595,0.001127281,0.0002932769,0.000385713,0.00038429,0.0002994244,0.0002774182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006398038,"about_ca_system_score_gemma":0.004032637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9429572,"about_ca_topic_score_gemma":0.941125,"domain_scores_codex":[0.999925,0.000009780792,0.000003552192,0.00001878828,0.00002136765,0.00002148468],"domain_scores_gemma":[0.9999111,0.00001357037,0.000008070245,0.000005386386,0.00004919671,0.0000126593],"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":[0.00005045009,0.00003319511,0.01541288,0.00001394692,0.00001693015,0.0001094359,0.000050842,0.9749742,0.0008870686,0.001167932,0.0006833143,0.006599805],"study_design_scores_gemma":[0.00001858867,0.000007478189,0.007216744,0.000004328143,0.00001082722,0.000009696804,0.00007600841,0.9911742,0.0002169306,0.0002594424,0.0009963724,0.00000937746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700987,0.0002812995,0.01055497,0.0002659666,0.00002649169,0.00005591533,0.002896367,0.000426221,0.01539414],"genre_scores_gemma":[0.9883653,0.0002019307,0.00545019,0.00001788336,0.00000516734,0.00002051209,0.001206437,0.00002733098,0.004705184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05704278,"threshold_uncertainty_score":0.1147574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940503618336212,"score_gpt":0.243640584363934,"score_spread":0.2242355481805719,"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."}}