{"id":"W2647966786","doi":"","title":"Evaluation of Ionospheric Interpolation Algorithms for Regional and National GPS Networks in Canada","year":2004,"lang":"en","type":"article","venue":"Proceedings of the 2004 National Technical Meeting of The Institute of Navigation","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Spherical harmonics; Algorithm; Geodesy; Geomagnetic storm; Spline (mechanical); Ionosphere; TEC; Interpolation (computer graphics); Spline interpolation; Grid; Computer science; Geology; Mathematics; Earth's magnetic field; Bilinear interpolation; Geophysics; Artificial intelligence; Mathematical analysis; Telecommunications; Physics","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":[0.002372968,0.0005785046,0.000469731,0.0009035596,0.0007623404,0.0007560436,0.001008225,0.0003203465,0.0008627524],"category_scores_gemma":[0.00709546,0.0002181786,0.0003540061,0.002055655,0.0002756379,0.0004710904,0.000490794,0.000327456,0.0001705056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008621211,"about_ca_system_score_gemma":0.008763575,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8222025,"about_ca_topic_score_gemma":0.7953924,"domain_scores_codex":[0.9991723,0.0001547493,0.00004153436,0.0001449785,0.0003306411,0.0001557049],"domain_scores_gemma":[0.99741,0.0005990854,0.0001761992,0.0001609003,0.001557458,0.00009629483],"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":[0.0004591359,0.00005762791,0.03310523,0.00005825796,0.00007264516,0.00004955089,0.00011966,0.8427695,0.001520726,0.001744113,0.001221306,0.1188223],"study_design_scores_gemma":[0.00003349208,0.00005055823,0.01209086,0.000009497879,0.00002407389,0.00002726465,0.0001258165,0.9847704,0.00170857,0.0002507584,0.0008949639,0.00001371127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8528506,0.0007108718,0.1340629,0.0002698999,0.00004277516,0.000188782,0.001422017,0.003234015,0.00721812],"genre_scores_gemma":[0.9118036,0.0002878063,0.08451936,0.00003107846,0.000007252195,0.0000493883,0.001696424,0.000108293,0.001496768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1777975,"threshold_uncertainty_score":0.3576891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693007612130887,"score_gpt":0.2611619675299632,"score_spread":0.2342318914086543,"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."}}