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Record W2150060642 · doi:10.5194/acp-7-1395-2007

MIPAS Level 1B algorithms overview: operational processing and characterization

2007· article· en· W2150060642 on OpenAlexaff
Anne Kleinert, Ginette Aubertin, Gaétan Perron, Manfred Birk, Georg Wagner, F. Hase, H. Nett, Robert H. Poulin

Bibliographic record

VenueAtmospheric chemistry and physics · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsABB (Canada)
Fundersnot available
KeywordsRadianceRemote sensingCalibrationEnvironmental scienceRange (aeronautics)Characterization (materials science)Radiometric calibrationNoise (video)Computer scienceMeteorologyOpticsPhysicsGeologyAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract. This paper gives an overview of the MIPAS Level 1B (L1B) processor whose main objective is to calibrate atmospheric measurements radiometrically, spectrally and geo-located. It presents also the results of instrument characterization done on ground and during the first years in-flight. An accurate calibration is mandatory for high quality atmospheric retrievals. MIPAS has shown very good performance and stability. The noise equivalent spectral radiance ranges from 3 to 50 nW/(cm2 sr cm−1) and is well within the requirements over nearly the whole spetral range. The systematic radiometric error is estimated to be within 1 or 2% in most situations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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.

Study designOther design
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

Citations66
Published2007
Admission routes1
Has abstractyes

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