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Record W6979267509

FINCH EYE: The Optical and Optomechanical Design of a GRISM-based SWIR Hyperspectral Imaging Payload for a 3U CubeSat

2025· article· en· W6979267509 on OpenAlexaboutno aff

Bibliographic record

VenueArXiv.org · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHyperspectral imagingCubeSatPayload (computing)Zebra finchBrightnessAerospaceFinchSatellite
DOInot available

Abstract

fetched live from OpenAlex

Crop residue is an important metric used for agricultural land-use monitoring and climate science research. Estimating crop residue coverage is essential to sustainable agricultural practices. The University of Toronto Aerospace Team is developing FINCH EYE, the optical payload for the upcoming FINCH 3U CubeSat, to measure crop residue cover. We conceived of a novel ultra-compact push-broom architecture with a volume phase-holographic grism dispersive element to keep the design compact and simplify the mechanical assembly. The FINCH EYE will image hyperspectral data from 900nm to 1700nm at 10nm spectral resolution, with a spatial resolution of 100m, and a SNR of 100. In this paper, we will describe the optical design of FINCH EYE, which consists of a commercial objective lens, an InGaAs camera, and a custom lens-grism-lens spectrograph. We will also describe the optomechanical housing, emphasizing design features that facilitate proper alignment during assembly.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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Same venueArXiv.orgSame topicSpacecraft Design and TechnologyFrench-language works237,207