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Record W4408426977 · doi:10.1088/1681-7575/adbcae

Comparison between four integer ambiguity resolved PPP GNSS time transfer software solutions

2025· article· en· W4408426977 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMetrologia · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsGNSS applicationsInteger (computer science)AmbiguityPrecise Point PositioningComputer scienceSoftwareTime transferGlobal Positioning SystemTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

Abstract We present a comparison between four different software solutions (dubbed PPP-AR or IPPP, all based on the resolution of integer ambiguities of the carrier-phase) that compute time links between GNSS receivers. Additional processing layers have been specially developed to enable usage for time transfer purposes. A variety of GNSS receivers connected to UTC(k) timescales across the globe, covering a wide range of baselines and several GNSS receiver models was used in this work. For one of the links, the availability of an optical fiber link between the stations allowed a comparison of each software-based GNSS link to this common reference, otherwise links were compared with each other using a specially-developed four-cornered hat algorithm. In the performance analysis we focused on the frequency stability of the time links. Results show that all four independently developed software solutions agree within 20 ps on TDEV for all averaging times and highlight the importance of mitigating day-boundary phase discontinuities. This demonstrates the reliability of the different implementations of the PPP-AR/IPPP technique for operational time transfer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.314
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it