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Record W2087049991 · doi:10.1080/01431160902893501

Two-dimensional tomographic retrieval of MIPAS/ENVISAT measurements of ozone and related species

2010· article· en· W2087049991 on OpenAlexaboutno aff
Enzo Papandrea, Enrico Arnone, Gabriele Brizzi, M. Carlotti, Elisa Castelli, B. M. Dinelli, Marco Ridolfi

Bibliographic record

VenueInternational Journal of Remote Sensing · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsAtmospheric soundingAtmosphere (unit)OzoneEnvironmental scienceDepth soundingRemote sensingMichelson interferometerAtmospheric sciencesNadirMeteorologySatelliteInterferometryGeologyPhysicsOptics

Abstract

fetched live from OpenAlex

Observations from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) were analysed with the two-dimensional GMTR retrieval system in order to obtain fields of ozone and several molecular species related to ozone chemistry: HNO3, N2O, NO2, N2O5, ClONO2, COF2, CFC-11 and CFC-12. MIPAS measures mid-infrared emission of the atmosphere both during the day and at night time with global coverage. Observing the atmosphere with limb viewing geometries, the instrument is able to resolve finer vertical structures than with nadir instruments, thus enabling the investigation of ozone height-dependent processes. With the currently planned mission extended up to 2014, MIPAS can provide both short-term resolution and long-term trends needed for studying ozone. The adopted GMTR algorithm permits us to resolve the horizontal inhomogeneities of the atmosphere that are modelled using a two-dimensional discretization of the atmosphere. It is therefore especially suitable for analysing portions of the atmosphere where strong gradients such as at the ozone hole may be poorly reproduced by common horizontal homogeneous one-dimensional retrievals. The adopted strategy is well suited for a refined analysis and a correct monitoring of the ozone recovery, as required by the Montreal Protocol and successive amendments.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.423

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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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

Citations14
Published2010
Admission routes1
Has abstractyes

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