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Record W2005760764 · doi:10.1088/0957-0233/24/1/015801

Design requirements for the SWIFT instrument

2012· article· en· W2005760764 on OpenAlexaff
Peyman Rahnama, William A. Gault, I. C. McDade, G. G. Shepherd

Bibliographic record

VenueMeasurement Science and Technology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
FundersEUROfusionIsrael Cancer Research Fund
KeywordsMichelson interferometerInterferometrySpacecraftRemote sensingSensitivity (control systems)VisibilityOptical path lengthOpticsDoppler effectAstronomical interferometerEnvironmental scienceFilter (signal processing)Optical instrumentSatelliteAerospace engineeringComputer sciencePhysicsEngineeringElectronic engineeringGeology

Abstract

fetched live from OpenAlex

The Stratospheric Wind Interferometer for Transport studies (SWIFT) instrument is a proposed limb-viewing satellite instrument that employs the method of Doppler Michelson interferometry to measure stratospheric wind velocities and ozone densities in the altitude range of 15–45 km. The values of the main instrument parameters including filter system parameters and Michelson interferometer parameters are derived using simulations and analyses. The system design requirements for the instrument and spacecraft are presented and discussed. Some of the retrieval-imposed design requirements are also discussed. Critical design issues are identified. The design optimization process is described. The sensitivity of wind measurements to instrument characteristics is investigated including the impact on critical design issues. Using sensitivity analyses, the instrument parameters were iteratively optimized in order to meet the science objectives. It is shown that wind measurements are sensitive to the thermal sensitivity of the instrument components, especially the narrow filter and the Michelson interferometer. The optimized values of the main system parameters including Michelson interferometer optical path difference, instrument visibility, instrument responsivity and knowledge of spacecraft velocity are reported. This work also shows that the filter thermal drift and the Michelson thermal drift are two main technical risks.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.089
GPT teacher head0.252
Teacher spread0.163 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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