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Record W3213663646 · doi:10.1088/1361-6501/ac3679

MiniCarb: a passive, occultation-viewing, 6U CubeSat for observations of CO <sub>2</sub> , CH <sub>4</sub> , and H <sub>2</sub> O

2021· article· en· W3213663646 on OpenAlexaff
E. L. Wilson, Vincent Riot, A. DiGregorio, Guru Ramu, Paul Cleveland, Lance M. Simms, Darrell Carter, B. Bruner, J. W. Young, Gerónimo Villanueva

Bibliographic record

VenueMeasurement Science and Technology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsLaurentian University
FundersLawrence Livermore National LaboratoryGoddard Space Flight Center
KeywordsCubeSatPayload (computing)Environmental scienceRemote sensingRadio occultationSatelliteOrbiterComputer scienceAerospace engineeringMeteorologyPhysicsTelecommunicationsEngineeringGlobal Positioning SystemGeology

Abstract

fetched live from OpenAlex

Abstract We present the final design, environmental testing, and launch history of MiniCarb, a 6U CubeSat developed through a partnership between NASA Goddard Space Flight Center and Lawrence Livermore National Laboratory. MiniCarb’s science payload, developed at Goddard, was an occultation-viewing, passive laser heterodyne radiometer for observing methane, carbon dioxide, and water vapor in Earth’s atmosphere at ∼1.6 µm s −1 . MiniCarb’s satellite, developed at Livermore, implemented their CubeSat Next Generation Bus plug-and-play architecture to produce a modular platform that could be tailored to a range of science payloads. Following the launch on 5 December 2019, MiniCarb traveled to the International Space Station and was set into orbit on 1 February 2020 via Northrop Grumman’s Cygnus capsule which deployed MiniCarb with tipoff rotation of about 20° s −1 (significantly higher than the typical rate of 3° s −1 from prior CubeSats), from which the attitude control system was unable to recover resulting in a loss of power. In spite of this early failure, MiniCarb had many successes including rigorous environmental testing, successful deployment of its solar panels, and a successful test of the radio and communication through the Iridium network. This prior work and enticing cost (approximately $2 M for the satellite and $250 K for the payload) makes MiniCarb an ideal candidate for a low-cost and rapid rebuild as a single orbiter or constellation to globally observe key greenhouse gases.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.229
Teacher spread0.204 · 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
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

Citations3
Published2021
Admission routes1
Has abstractyes

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