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Record W2063396714 · doi:10.5194/amt-5-2447-2012

Level 1 algorithms for TANSO on GOSAT: processing and on-orbit calibrations

2012· article· en· W2063396714 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAtmospheric measurement techniques · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsABB (Canada)
Fundersnot available
KeywordsRadianceSatelliteRemote sensingCalibrationEnvironmental scienceSpectrometerSpectral resolutionMethaneGreenhouse gasPhysicsComputer scienceOpticsSpectral lineGeologyAstronomy

Abstract

fetched live from OpenAlex

Abstract. The Thermal And Near infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT) (nicknamed "Ibuki") has been providing global space-borne observations of carbon dioxide (CO2) and methane (CH4) since 2009. In this paper, we first describe the version V150.151 operational Level 1 algorithms that produce radiance spectra from the acquired interferograms. Second, we will describe the on-orbit characteristics and calibration of TANSO-FTS. Overall function and performance such as signal to noise ratio and spectral resolution are within design objectives. Correction methods of small on-orbit degradations and anomalies, which have been found since launch, are described. Lastly, calibration of TANSO Cloud and Aerosol Imager (TANSO-CAI) are summarized.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.056
GPT teacher head0.260
Teacher spread0.205 · 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