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Record W2052724495 · doi:10.1002/joc.1966

UV‐B cloud optical properties for Canada

2009· article· en· W2052724495 on OpenAlexaffabout
Jacqueline Binyamin, John Davies, Bruce McArthur

Bibliographic record

VenueInternational Journal of Climatology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsMcMaster UniversityUniversity of Winnipeg
Fundersnot available
KeywordsOvercastCloud albedoOptical depthAlbedo (alchemy)Environmental scienceEffective radiusAtmospheric sciencesIrradianceRadiative transferSingle-scattering albedoAERONETAtmospheric radiative transfer codesSnowArcticLatitudeSolar zenith angleCloud coverMiddle latitudesCloud topClimatologyAerosolMeteorologyCloud computingPhysicsSkySatelliteGeographyGeologyAstrophysicsGeodesyOptics

Abstract

fetched live from OpenAlex

Abstract Cloud optical properties play a highly significant role in the amount of UV‐B irradiance reaching the ground. Broadband values of UV‐B cloud optical properties are calculated for nine Canadian stations from 26 years of data. Cloud single scattering albedo ωc and asymmetry factor gc are computed from Mie theory for two values of equivalent droplet radius; 7 µm for arctic stations and 10 µm for midlatitude and subarctic stations. Overcast cloud optical depths τc are estimated iteratively for a model cloud layer located between 2 and 3 km above the surface from hourly integrated spectral Brewer spectrophotometer measurements for snow‐free cases using either the discrete ordinate radiative transfer (DISORT) or the delta‐Eddington algorithms. Median τc values calculated by both algorithms compare to within 3%. Median values are smaller for arctic stations (9–18) and between 26 and 38 for the rest. Both mean and median values are negatively correlated with latitude. Aerosol effect on τc varies between 9 and 18% on average. Copyright © 2009 Royal Meteorological Society

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.244
Teacher spread0.233 · 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

Citations10
Published2009
Admission routes2
Has abstractyes

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