MétaCan
Menu
Back to cohort

Onboard calibration and monitoring for the SWIFT instrument

2012· article· en· W2026866889 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
Fundersnot available
KeywordsCalibrationMichelson interferometerRemote sensingSwiftInterferometryDoppler effectOpticsPhysicsPhase (matter)Environmental scienceComputer scienceGeology

Abstract

fetched live from OpenAlex

The SWIFT (Stratospheric Wind Interferometer for Transport studies) instrument is a proposed space-based field-widened Doppler Michelson interferometer designed to measure stratospheric winds and ozone densities using a passive optical technique called Doppler Michelson imaging interferometry. The onboard calibration and monitoring procedures for the SWIFT instrument are described in this paper. Sample results of the simulations of onboard calibration measurements are presented and discussed. This paper also discusses the results of the derivation of the calibrations and monitoring requirements for the SWIFT instrument. SWIFT's measurement technique and viewing geometry are briefly described. The reference phase calibration and filter monitoring for the SWIFT instrument are two of the main critical design issues. In this paper it is shown that in order to meet SWIFT's science requirements, Michelson interferometer optical path difference monitoring corresponding to a phase calibration accuracy of ∼10−3 radians, filter passband monitoring corresponding to phase accuracy of ∼5 × 10−3 radians and a thermal stability of 10−3 K s−1 are required.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.044
GPT teacher head0.233
Teacher spread0.189 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMeasurement Science and TechnologySame topicAtmospheric Ozone and ClimateFrench-language works237,207