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Record W2937196756 · doi:10.5683/sp/cwj2vh

Replication Data for: Tightly-Coupled GNSS/Vision using a Sky-pointing Camera for Vehicle Navigation in Urban Areas

2018· article· en· W2937196756 on OpenAlexaff
Paul Verlaine Gakne, Kyle O’Keefe

Bibliographic record

VenueBorealis · 2018
Typearticle
Languageen
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGNSS applicationsSkyComputer scienceReplication (statistics)Computer visionRemote sensingArtificial intelligenceGlobal Positioning SystemGeographyTelecommunicationsMeteorology

Abstract

fetched live from OpenAlex

This dataset contains GPS RINEX 2.11 format files for GPS observations made by the test vehicle, a text file containing the reference trajectory of the test vehicle, and a series of video frames spanning the same time period as the GPS data and the reference trajectory described in the paper: Tightly-Coupled GNSS/Vision using a Sky-pointing Camera for Vehicle Navigation in Urban Areas, published in Sensors, doi:10.3390/s18041244

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.043
GPT teacher head0.323
Teacher spread0.280 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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