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Record W4401799574 · doi:10.1117/12.3034022

TESERACT: twin Earth sensor astrophotonic CubeSat

2024· article· en· W4401799574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsNational Research Council CanadaAlgonquin CollegeCarleton University
Fundersnot available
KeywordsCubeSatEarth (classical element)Computer scienceAstrobiologyEarth observationAerospace engineeringEngineeringPhysicsAstronomySatellite

Abstract

fetched live from OpenAlex

In this paper, we evaluate the viability of Cubesats as an attractive platform for lightweight instrumentation by describing a proof of concept CubeSat that houses an astrophotonic chip for transit spectroscopy-based exoplanet atmosphere gas sensing. The Twin Earth SEnsoR Astrophotonic CubesaT (TESERACT) was designed to house a correlation spectroscopy chip along with an electrical and optical system for operation. We investigate design challenges and considerations in incorporating astrophotonic instrumentation such as component integration, thermal management and optical alignment. This work aims to be a pathfinder for demonstrating that astrophotonic-based CubeSat missions can perform leading edge, targeted science in lower-cost CubeSat platforms.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score1.000

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)0.0010.002

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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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