{"id":"W2148962069","doi":"10.1109/plans.2002.998898","title":"Strategies for estimating tropospheric delays with GPS","year":2003,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Global Positioning System; Geodetic datum; Computer science; Process (computing); Environmental science; Remote sensing; Geography; Telecommunications; Geodesy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006419558,0.0009785015,0.0005611139,0.001542295,0.0004537948,0.0009146272,0.0009337902,0.0004280784,0.002152281],"category_scores_gemma":[0.002582717,0.0004324674,0.0003971941,0.001448771,0.000301243,0.0009781244,0.0009400115,0.000547032,0.001297457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003970464,"about_ca_system_score_gemma":0.0007619612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00916243,"about_ca_topic_score_gemma":0.009790637,"domain_scores_codex":[0.9996525,0.00009883293,0.0000194541,0.00006926701,0.0001318037,0.00002817804],"domain_scores_gemma":[0.9996455,0.0001448411,0.00003170043,0.00005796648,0.0001074646,0.00001250098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000212055,0.00003925037,0.004750233,0.0001898105,0.0000921867,0.0001203327,0.0002800646,0.1922866,0.0187505,0.02956848,0.002627772,0.7510827],"study_design_scores_gemma":[0.0001053436,0.0002501105,0.006195221,0.00009528136,0.0002074854,0.0003791328,0.0003373424,0.8713328,0.03285592,0.03832487,0.04978842,0.0001281417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007907885,0.0003512354,0.9888386,0.00005850421,0.00002628179,0.00004689304,0.00009279032,0.0004173246,0.002260549],"genre_scores_gemma":[0.1554274,0.0008523488,0.8393907,0.00003105345,0.00005438125,0.0001225438,0.0004420081,0.0001220812,0.003557518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00916243,"threshold_uncertainty_score":0.01821822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009893149532938069,"score_gpt":0.2107781451018392,"score_spread":0.2008849955689011,"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."}}