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Record W2121779639 · doi:10.1109/taes.2011.5937267

GNSS Modulation: A Unified Statistical Description

2011· article· en· W2121779639 on OpenAlexaff
F. Cote, Ioannis Psaromiligkos, Warren J. Gross

Bibliographic record

VenueIEEE Transactions on Aerospace and Electronic Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsMcGill University
Fundersnot available
KeywordsGNSS applicationsComputer scienceModulation (music)Remote sensingRadar trackerTelecommunicationsGlobal Positioning SystemElectronic engineeringRadarEngineeringGeographyPhysicsAcoustics

Abstract

fetched live from OpenAlex

A unifying framework for all signals employed by the Global Positioning System (GPS) and Galileo system is presented. The framework reconciles split-spectrum modulations under a single analytical formulation. The formulation allows for the derivation of closed-form equations for the autocorrelation function (ACF) and power spectral density (PSD) containing, as special cases, the corresponding functions for GPS and Galileo signals. Simulation studies and comparisons with existing expressions demonstrate the generality and accuracy of the proposed statistical description.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.023
GPT teacher head0.202
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations17
Published2011
Admission routes1
Has abstractyes

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