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Record W6963646041 · doi:10.21227/5v28-w131

Real GPS Data collected in Downtown Ottawa

2023· dataset· en· W6963646041 on OpenAlexaffabout

Bibliographic record

VenueIEEE DataPort · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsCarleton University
Fundersnot available
KeywordsGNSS applicationsData fileGlobal Positioning SystemDowntownProduct (mathematics)Satellite

Abstract

fetched live from OpenAlex

This file contains real GNSS data collected from a suburban region to a dense urban region in Ottawa. For the interest of the work, only GPS data are collected. The data are collected using two Ublox GNSS units (receivers), namely EVK-M8T and EVK-M8U. EVK-M8T is a timing product that can provide precise timing information for post-processing. EVK-M8U is a product that features dead reckoning mode, making this product reliable even in urban canyons. The data are in the format of UBX, NAV, and OBS. The UBX file is outputed directly by the receiver using u-center (software). The NAV file is converted from the UBX file using RTKLIB, which is an open source program package for GNSS positioning. This file contains data about satellite navigation messages, such as the Keplerian parameters, the ionospheric parameters, etc. The OBS file is also converted from the UBX file using RTKLIB.This file contains the observations about satellite, such as pseudorange, PRN code, etc. 

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), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.187
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0100.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.189

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 head0.082
GPT teacher head0.350
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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes2
Has abstractyes

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