{"id":"W2066915909","doi":"10.1515/jag.2011.004","title":"Impact of second-order ionospheric delay on GPS precise point positioning","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Geodesy","topic":"GNSS positioning and interference","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pseudorange; Global Positioning System; Geodesy; Precise Point Positioning; Ionosphere; Group delay and phase delay; Satellite; Residual; GPS signals; Physics; Computer science; Assisted GPS; Geography; Telecommunications; GNSS applications; Algorithm; Geophysics; Bandwidth (computing)","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":[0.0006494444,0.0008833517,0.0004781013,0.0005515671,0.0003782757,0.0007166489,0.0003126728,0.0006001956,0.001522236],"category_scores_gemma":[0.00325055,0.0002573821,0.0005500795,0.0008935963,0.0003185621,0.0005446048,0.0005153961,0.0005930074,0.0003554683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007346604,"about_ca_system_score_gemma":0.0008652721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009998819,"about_ca_topic_score_gemma":0.007693634,"domain_scores_codex":[0.9993287,0.0001284758,0.00002901596,0.0001121239,0.0002494651,0.0001522057],"domain_scores_gemma":[0.9976799,0.001604327,0.0001466852,0.0002257097,0.0002896377,0.00005386844],"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":[0.001513271,0.0001439145,0.05267655,0.0007256138,0.0003195782,0.002921481,0.0008981275,0.6947917,0.1424703,0.006186675,0.00163731,0.09571553],"study_design_scores_gemma":[0.0001024413,0.001023784,0.06844573,0.0001075316,0.0004126076,0.003666537,0.0004646619,0.7577192,0.1534132,0.002387878,0.01209025,0.0001661694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7961565,0.002349486,0.1917156,0.0002960157,0.0005104975,0.00004315795,0.0006313772,0.001260762,0.007036456],"genre_scores_gemma":[0.9914109,0.0007838954,0.005612751,0.00005156858,0.00003791775,0.00001176186,0.0002949577,0.0001883816,0.001607762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009998819,"threshold_uncertainty_score":0.01988125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242171662607416,"score_gpt":0.2203902924570219,"score_spread":0.2079685758309478,"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."}}