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Record W1883701165 · doi:10.1002/2013jd020480

Spectral calibration and validation of the Cross‐track Infrared Sounder on the Suomi NPP satellite

2013· article· en· W1883701165 on OpenAlexaff
L. Larrabee Strow, Howard E. Motteler, David C. Tobin, Henry E. Revercomb, S. Hannon, Henry Buijs, Joe Predina, Lawrence Suwinski, Ronald J. Glumb

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2013
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsABB (Canada)
Fundersnot available
KeywordsCalibrationRemote sensingApodizationSatelliteDetectorEnvironmental scienceInfraredTrack (disk drive)Radiometric calibrationOpticsStability (learning theory)PhysicsComputer scienceGeology

Abstract

fetched live from OpenAlex

The Cross‐track Infrared Sounder (CrIS) radiometric accuracy depends upon accurate frequency calibration. Here we present both the prelaunch calibration of the sensor and the minor modifications needed to this calibration post launch. Particular emphasis is given to ensuring that all nine detectors on each of the three CrIS focal planes are on a common frequency scale with accurate off‐axis apodization corrections. Radiances from the current operational algorithm have a frequency calibration that is stable to 2 ppm, although this work suggests that the CrIS instrument is capable of a frequency calibration stability of better than 1 ppm.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.301
Teacher spread0.259 · 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

Citations82
Published2013
Admission routes1
Has abstractyes

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