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Record W4401807463 · doi:10.1117/12.3020559

CuRIOS-ED: the technology demonstrator for the CubeSats for rapid infrared and optical surveys mission

2024· article· en· W4401807463 on OpenAlexaboutno aff
Hannah Gulick, Jessica R. Lu, Aryan Sood, S. V. W. Beckwith, J. S. Bloom, Kodi Rider, Dan Werthimer, Wei Liu, Guy Nir, Harrison Lee, Jeremy McCauley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsInfraredAeronauticsAerospace engineeringSystems engineeringRemote sensingComputer scienceEngineeringPhysicsAstronomyGeology

Abstract

fetched live from OpenAlex

To address the need for surveys with high-cadence, large area, and long time baselines to study the transient universe, we intend to launch CuRIOS (CubeSats for Rapid Infrared and Optical Surveys), a constellation of several hundred 16U CubeSats that will provide all-sky, all-the-time observations to a depth of 21 Vega magnitudes in the optical bandpass. A CuRIOS technology demonstrator, known as the CuRIOS-Exploration Demo (CuRIOS-ED), is slated to launch in 2025 as part of the 12U payload. CuRIOS-ED will be used to space-qualify a commercial camera package—the Atik apx60 with Sony IMX455 CMOS detector—for use on the full CuRIOS payload. In this presentation, we discuss the CuRIOS-ED mission design with an emphasis on the disassembly, repackaging, and testing of the Atik apx60 for space-based. The testing results will include characterization of the IMX455 detector and Atik electronics performance, as well as preliminary environmental testing results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0240.013

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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