{"id":"W2891752863","doi":"10.1007/1345_2018_43","title":"Comparing the Nigerian GNSS Reference Network’s Zenith Total Delays from Precise Point Positioning to a Numerical Weather Model","year":2018,"lang":"en","type":"book-chapter","venue":"International Association of Geodesy symposia","topic":"GNSS positioning and interference","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Zenith; GNSS applications; Numerical weather prediction; Meteorology; Precise Point Positioning; Environmental science; Standard deviation; Satellite; Satellite system; Weather Research and Forecasting Model; Remote sensing; Geodesy; Geography; Mathematics; Engineering; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002798999,0.0003914897,0.0004596096,0.0001326651,0.0001471001,0.0001932059,0.0005834991,0.0003441493,0.0006175545],"category_scores_gemma":[0.00005167835,0.0003736528,0.0002019537,0.0000557539,0.00004052838,0.0002049355,0.0001601143,0.0005265255,0.000364523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009887015,"about_ca_system_score_gemma":0.00005454946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001279117,"about_ca_topic_score_gemma":0.00008063806,"domain_scores_codex":[0.9977762,0.00003735785,0.0007250397,0.00039303,0.0007378851,0.0003305395],"domain_scores_gemma":[0.9983832,0.0002159906,0.0004167759,0.0003234593,0.0005461671,0.0001143539],"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":[0.0001935827,0.00007369056,0.001815369,0.00002553958,0.002018397,0.000004387587,0.003123791,0.8586635,0.002016588,0.07699387,0.05445058,0.0006207168],"study_design_scores_gemma":[0.0007274934,0.0001948573,0.003525001,0.001885052,0.0002766179,0.00001924056,0.0000528251,0.9505445,0.0006990585,0.02503844,0.01588014,0.001156732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03719229,0.0001969584,0.07167706,0.001197359,0.002118562,0.0005595223,0.0008214126,0.0004024818,0.8858343],"genre_scores_gemma":[0.93563,0.00003709945,0.002100213,0.0002074264,0.0007606893,0.00004534707,0.0004636273,0.00009145118,0.06066418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8984377,"threshold_uncertainty_score":0.9998716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014009858143648,"score_gpt":0.2142918157433408,"score_spread":0.2002819575996928,"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."}}