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Record W7155199517 · doi:10.46326/jmes.2025.66(5).08

Determining the displacement velocity of some continuously operating reference stations (CORS) in Vietnam in the period 2019÷2024 using the Precise Point Positioning method

2025· article· vi· W7155199517 on OpenAlexaboutno aff
Lau Ngoc Nguyen, Vu Dinh Trinh

Bibliographic record

VenueJournal of Mining and Earth Sciences · 2025
Typearticle
Languagevi
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsPrecise Point PositioningDisplacement (psychology)GNSS applicationsTectonicsStandard deviationVertical displacementPoint (geometry)

Abstract

fetched live from OpenAlex

Precise knowledge of tectonic motion allows us to better understand the mechanism of Earth's crustal deformation and dynamics. The modern method commonly used to determine the velocity of tectonic plate movement today is Precise Point Positioning (PPP). We use the online service of the Canadian Ministry of Natural Resources CSRS - PPP to process GNSS data of 12 Continuously Operating Reference Stations (CORS) in Vietnam during the period 2019÷2024. These CORSs are managed by Tuong Anh Company and are evenly distributed throughout the territory. The PPP processing results show that the time series of the North, East and Up components of the CORS stations fluctuate with a period of approximately 1 year. After modeling this variation with a sine function with a fixed period of 351.6 days, we calculated the average displacement velocity of the stations as (-8.8, +29.6, -3.1) mm/year in the North, East and Up components. Compared to the period 2019÷2022, the displacement velocity of the tectonic plate is almost unchanged in direction and magnitude. The deviation in the horizontal components is 1 mm/year and the Up is 1.6 mm/year. In order to avoid possible effects due to the conversion of the ITRF 2014 to ITRF 2020 on November 27, 2022, we calculated the displacement velocity for the period 12/2022÷9/2024. This result gives an average deviation compared to the period 2019÷2024 in the horizontal and up components of 1mm/year and 3mm/year. It proves the model fit and the correctness of the applied coordinate transformation parameter set.

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.

How this classification was reachedexpand

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.319
Teacher spread0.269 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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