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Record W2139720086 · doi:10.5897/sre11.1885

Kinematic GNSS-PPP results from various software packages and raw data configurations

2012· article· en· W2139720086 on OpenAlexaboutno aff
Ángel Martín, Ana Belén Anquela Julián, J. L. Berné, Miriam Sanmartin

Bibliographic record

VenueRiuNet (Politechnical University of Valencia) · 2012
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsGNSS applicationsPrecise Point PositioningSoftwareGlobal Positioning SystemComputer scienceKinematicsReal Time KinematicReal-time computingTrajectoryGeodesyRemote sensingGeographyTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

[EN] In this study, kinematic precise point positioning (PPP) was tested. The raw data were taken from permanent stations, two airplane trajectories, a car trajectory and a walking trajectory. International GNSS Service (IGS) final products were used in the post-processing phase. The observations were processed using four different on-line software packages: the Canadian Spatial Reference System On-line Global GPS Processing Service (CSRS-PPP), the GPS Analysis and Position Software (GAPS), the Automatic Precise Positioning Service (APPS) and the Magic Global Navigation Satellite System (MagicGNSS). The results and comparisons are described in detail. The main conclusion is that an accuracy better than 10 cm for the planimetric measurements and better than 20 cm for the altimetric measurements can be achieved using the kinematic PPP method in any of the proposed tests. However, at present, the success of the technique is affected by the software used, and differences at the 0.5 m level can be found for the same specific epoch.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.572

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)0.0000.000

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 head0.034
GPT teacher head0.220
Teacher spread0.186 · 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

Citations27
Published2012
Admission routes1
Has abstractyes

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