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Record W6944780008 · doi:10.21227/rxs9-q120

Source Code and Dataset associated with "Realistic Channel and Delay Coefficient Generation for Dual Mobile Space-Ground Links -- A Tutorial"

2024· dataset· en· W6944780008 on OpenAlexaff

Bibliographic record

VenueIEEE DataPort · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsCarleton University
Fundersnot available
KeywordsChannel (broadcasting)Code (set theory)Global Positioning SystemSource codeDoppler effectGNSS applicationsSIGNAL (programming language)GPS signalsCode division multiple access

Abstract

fetched live from OpenAlex

The source code includes the modified version of QuaDRiGa source code, the scritps that we developed to generate the layout and the channel and delay coefficients for the dual mobile space-ground links. We integrate a practical phenomenon in signal reception by employing both a LOS probability model and a state transition model which follows the semi-Markov approach. We also provide our source code which can be used to not only analyze the Doppler spectrum, delay spread, received signal power, based on the generated channel and delay coefficients, but also generate a pseudo signals for GPS satellites. As a courtesy, we provide a dataset containing the GPS positions generated using the Skydel GNSS Simulation Software. 

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.025
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.037
GPT teacher head0.298
Teacher spread0.261 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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