{"id":"W2094590854","doi":"10.1007/s10291-013-0334-8","title":"Assessment of troposphere mapping functions using three-dimensional ray-tracing","year":2013,"lang":"en","type":"article","venue":"GPS Solutions","topic":"GNSS positioning and interference","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"GNSS applications; Troposphere; Geodetic datum; Ray tracing (physics); Calibration; Remote sensing; Computer science; Function (biology); Algorithm; Set (abstract data type); Precise Point Positioning; Data set; Geodesy; Meteorology; Global Positioning System; Geography; Mathematics; Artificial intelligence; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012613,0.0006372238,0.0002264683,0.001030654,0.0003189563,0.0008753042,0.0003903234,0.0005473736,0.000925735],"category_scores_gemma":[0.003270843,0.0001565504,0.0002875857,0.0007452019,0.0002517908,0.0005081548,0.000418112,0.0002713214,0.0002962468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005103236,"about_ca_system_score_gemma":0.0007118067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01122491,"about_ca_topic_score_gemma":0.006077588,"domain_scores_codex":[0.9997066,0.00009383414,0.0000126272,0.00002844103,0.0001202722,0.00003825688],"domain_scores_gemma":[0.99836,0.0007209796,0.00009659783,0.0001649738,0.0005762602,0.0000812006],"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":[0.001000354,0.0002355765,0.05827446,0.0001359205,0.0000976274,0.0002460639,0.000452096,0.697054,0.04909176,0.002983568,0.0006726395,0.1897559],"study_design_scores_gemma":[0.00002940168,0.0001982358,0.0395247,0.00001538724,0.00004528279,0.000095806,0.0001345474,0.9390728,0.01951715,0.0005531277,0.0007822543,0.00003133353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7993668,0.0001703706,0.1930073,0.00008407336,0.00001505465,0.00006932762,0.000499352,0.001263309,0.005524337],"genre_scores_gemma":[0.9721196,0.00006706066,0.02695156,0.000005748338,0.000002186065,0.00001421073,0.000199273,0.00005077447,0.0005895449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01122491,"threshold_uncertainty_score":0.02231914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02885038539248342,"score_gpt":0.2415519301813076,"score_spread":0.2127015447888242,"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."}}