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Record W2005147144 · doi:10.1117/12.508011

Characterization of composition, size, and density of atmospheric aerosols from high-resolution IR satellite measurements

2003· article· en· W2005147144 on OpenAlexaff
A. Y. Zasetsky, J. J. Sloan

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSatelliteAerosolAtmosphere (unit)Characterization (materials science)Environmental scienceExtinction (optical mineralogy)Atmospheric sciencesAtmospheric compositionSpectroscopyRemote sensingMaterials scienceMeteorologyChemistryMineralogyPhysicsGeology

Abstract

fetched live from OpenAlex

We describe a new method for the quantitative characterization of condensed phases in the atmosphere. It uses broad band IR extinction spectra to obtain the density, size distribution, phase and the approximate composition of aerosols within a single retrieval process. The method is based on a linear least squares fitting procedure with physically-based constraints. In this report, the method is applied to the analysis of spectra measured by the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument. The volume density, size distribution and composition of the stratospheric sulfate aerosols observed in several ATMOS missions are reported. The values of these properties for aerosols observed shortly after the eruption of Mount Pinatubo in 1992 are compared with those of aerosols present at much lower levels in 1993 and 1994.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.195
Teacher spread0.184 · 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 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

Citations1
Published2003
Admission routes1
Has abstractyes

Explore more

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