{"id":"W2162889446","doi":"10.1002/j.2161-4296.2007.tb00400.x","title":"Dual-Frequency GPS Precise Point Positioning with WADGPS Corrections","year":2007,"lang":"en","type":"article","venue":"NAVIGATION Journal of the Institute of Navigation","topic":"GNSS positioning and interference","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Global Positioning System; Computer science; Precise Point Positioning; Smoothing; Satellite; Differential GPS; Pseudorange; Dual (grammatical number); Noise (video); Point (geometry); GPS disciplined oscillator; Process (computing); Real-time computing; GPS signals; Assisted GPS; Telecommunications; GNSS applications; Computer vision; Mathematics; Engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005457799,0.0006246551,0.0004528588,0.0006739798,0.0002233016,0.000601912,0.0008384902,0.0003984038,0.002395327],"category_scores_gemma":[0.002541841,0.0003683825,0.0003902239,0.001037165,0.0002265858,0.0005398163,0.0007995051,0.0006566941,0.002271494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002858922,"about_ca_system_score_gemma":0.0005779788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001866483,"about_ca_topic_score_gemma":0.003074787,"domain_scores_codex":[0.9991785,0.0001147571,0.00004043572,0.0001487668,0.0004705786,0.00004696418],"domain_scores_gemma":[0.9991515,0.0001402528,0.0001025624,0.0002352808,0.000349483,0.00002095218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000941015,0.0001716968,0.02646713,0.0003850161,0.0001847372,0.0002088268,0.000260673,0.1478354,0.2265064,0.006196482,0.003205301,0.5876372],"study_design_scores_gemma":[0.0001324366,0.0003877691,0.0153988,0.00003574667,0.0001329678,0.0004870615,0.00006363581,0.7647727,0.1932646,0.003106468,0.0221465,0.00007130258],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0447342,0.00004594245,0.9518356,0.00004442016,0.00004947952,0.00006063462,0.0001710005,0.001764945,0.001293874],"genre_scores_gemma":[0.2946745,0.00008566005,0.7006929,0.00002965686,0.00002616727,0.0001036539,0.0005994655,0.0001314752,0.003656482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002395327,"threshold_uncertainty_score":0.008013189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008394091341673394,"score_gpt":0.227641857954144,"score_spread":0.2192477666124706,"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."}}