{"id":"W3112519502","doi":"10.1186/s43020-020-00030-y","title":"Improved precise positioning with BDS-3 quad-frequency signals","year":2020,"lang":"en","type":"article","venue":"Satellite Navigation","topic":"GNSS positioning and interference","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Ambiguity resolution; Precise Point Positioning; Geodesy; Computer science; Baseline (sea); Global Positioning System; BeiDou Navigation Satellite System; Constellation; GNSS applications; Satellite; Remote sensing; Real-time computing; Geography; Geology; Telecommunications; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.00005934242,0.000145137,0.0001271857,0.00003028997,0.00007253648,0.00009413659,0.00009882521,0.00006682973,0.00004447033],"category_scores_gemma":[0.00001148074,0.0001380638,0.00003428462,0.0002271263,0.00002598025,0.0003143286,0.000008211727,0.0001862029,0.000110385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004945911,"about_ca_system_score_gemma":0.00001412363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002132739,"about_ca_topic_score_gemma":0.000001938733,"domain_scores_codex":[0.9992552,0.00002387791,0.0002095792,0.0001915863,0.0001334509,0.000186299],"domain_scores_gemma":[0.9996204,0.00002674658,0.00004168709,0.0001199463,0.00008495474,0.0001062864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007433708,0.00003103921,0.001663708,0.0002691888,0.00009075834,0.00001213074,0.004778292,0.01645937,0.9479367,0.001194778,0.0001633635,0.02732635],"study_design_scores_gemma":[0.001289951,0.001070885,0.00731631,0.001306727,0.0001217344,0.00004989524,0.000415983,0.1987477,0.7851166,0.00230834,0.001135761,0.001120141],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9151813,0.001290522,0.06041052,0.0003844612,0.0001849211,0.0003682599,0.0000269491,0.001054573,0.02109845],"genre_scores_gemma":[0.9958377,0.00005709383,0.003633434,0.0001071236,0.0001158076,0.00002519581,0.0001627973,0.00003126103,0.0000296189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1822884,"threshold_uncertainty_score":0.5630078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121125653976194,"score_gpt":0.2071572117030485,"score_spread":0.1959459551632866,"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."}}