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Record W2057193063 · doi:10.1139/p07-089

The impact of sea-glint upon limb radiance

2007· article· en· W2057193063 on OpenAlexafffundvenue
D. A. Degenstein, Adam Bourassa, E. J. Llewellyn, N. D. Lloyd

Bibliographic record

VenueCanadian Journal of Physics · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Space Agency
KeywordsRadiancePhysicsZenithRemote sensingRadiative transferWavelengthSatelliteSpectrographOpticsAtmospheric radiative transfer codesAstronomySpectral lineGeology

Abstract

fetched live from OpenAlex

A simple radiative transfer model is developed to calculate the contribution of sea-glint to limb radiance. It is shown that the absolute sea-glint signal peaks between 70° and 80° solar zenith angle. Sea-glint can contribute 10–15% of the total limb radiance at wavelengths greater than 600 nm, which is several times brighter than an equivalent 5% reflecting Lambertian ocean surface. A test case was identified over the Arabian Sea in October 2002 and the model results compared to limb observations from the Optical Spectrograph and Infra-Red Imaging System (OSIRIS) on-board the Odin satellite. PACS Nos.: 94.10.Gb, 93.85.+q, 42.68.Ay, 42.68.Mj

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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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
Published2007
Admission routes3
Has abstractyes

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