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Record W7110800952 · doi:10.26077/d8f8-y546

NIORD: A Compact High-Resolution Low-Light Imager for Marine Traffic Surveillance

2025· other· W7110800952 on OpenAlexaff

Bibliographic record

VenueDigital Commons - USU (Utah State University) · 2025
Typeother
Language
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCatadioptric systemSpacecraftProcess (computing)Space (punctuation)Spacecraft designNorwegian

Abstract

fetched live from OpenAlex

NIORD is a compact high-resolution low-light imager for marine traffic surveillance. It will be used by the Norwegian Defense Research Establishment (FFI) on the NorSat-4 satellite, which is owned by the Norwegian Space Agency. This imager is based on a catadioptric optical design fully integrated at SAFRAN Reosc. Its integration on the spacecraft was performed in May 2023 at UTIAS Space Flight Laboratory. This paper develops the project life cycle, from the opto-mechanical design to the integration process and tests performed on the instrument.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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