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Record W3109257457

GPS and Galileo Performance Evaluations for Multiple Reference Network Real-Time Positioning

2006· article· en· W3109257457 on OpenAlexaboutno aff
S. Phalke, M. Elizabeth Cannon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemGalileo (satellite navigation)Ambiguity resolutionGNSS applicationsPrecise Point PositioningComputer scienceBaseline (sea)Real Time KinematicRemote sensingReal-time computingSatellite systemSatelliteGeodesyGeographyTelecommunicationsEngineeringAerospace engineeringGeology
DOInot available

Abstract

fetched live from OpenAlex

of Calgary. She has been involved with GPS research since 1984 and has published numerous papers on static and kinematic positioning. She is a Past President of the ION and the recipient of the 2001 Kepler Award. She currently serves as the ION Satellite Division Chair. The European Galileo system and the modernization of the current Global Positioning System (GPS) will substantially increase the available signals to Global Navigation Satellite Systems (GNSS) users. Past simulation studies have shown that Galileo performs better than GPS for high ionospheric conditions and for medium length baselines for the Single Reference Station (SRS) approach. When the baseline increases beyond 30 km, the ambiguity resolution performance deteriorates,

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.404

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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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 designSimulation or modeling
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

Citations1
Published2006
Admission routes1
Has abstractyes

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