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Record W2124402446 · doi:10.1139/p01-152

A method for recovering stratospheric minor species densities from the Odin/OSIRIS scattered-sunlight measurements

2002· article· en· W2124402446 on OpenAlexafffundvenue
I. C. McDade, Kimberly Strong, C. S. Haley, J. Stegman, D. Murtagh, E. J. Llewellyn

Bibliographic record

VenueCanadian Journal of Physics · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsOsirisPhysicsDifferential optical absorption spectroscopyStratosphereSunlightSatelliteSpectrographRemote sensingRange (aeronautics)OccultationOpticsAbsorption (acoustics)Spectral lineAtmospheric sciencesAstrophysicsAstronomyMaterials scienceGeology

Abstract

fetched live from OpenAlex

A method for recovering minor species density profiles in the stratosphere from observations made with the OSIRIS (optical spectrograph and infrared imager system) instrument on the Odin satellite is described. The OSIRIS instrument measures limb radiances of scattered sunlight over the spectral range 2800 to 8000 Å, for tangent heights ranging from 10 to 100 km. We describe how the limb spectra may be processed using the DOAS (differential optical absorption spectroscopy) technique to derive apparent column densities for the minor atmospheric constituents O3, NO2, OClO, and BrO. We also show how these column densities, measured over a range of tangent heights, may be inverted using an iterative least-squares technique to determine the local density profiles. The procedures are illustrated using simulated limb radiances generated with a realistic OSIRIS instrument model. PACS Nos.: 42.68Mj, 94.10Dy

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.069
GPT teacher head0.222
Teacher spread0.154 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations16
Published2002
Admission routes3
Has abstractyes

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