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Record W2069968494 · doi:10.1029/2001jd001559

On the features of clouds occurring over the Mackenzie River basin

2002· article· en· W2069968494 on OpenAlexaffabout
Ronald E. Stewart, Jason E. Burford

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsYork University
Fundersnot available
KeywordsCloud coverEnvironmental scienceCloud fractionClimatologyScale (ratio)Cloud computingStructural basinAtmospheric sciencesGeologyGeographyGeomorphologyCartography

Abstract

fetched live from OpenAlex

To better characterize the occurrence of clouds and some of their features over the Mackenzie basin of northwestern Canada, surface‐based measurements of cloud fields have been examined from several operational observing sites. This article focuses on the determination of cloud cover fraction, cloud base height, multiple layering, and cloud type as well as the variations of these on temporal scales ranging from diurnal to interannual. In addition, the cloud features were related to the large‐scale circulation, large‐scale convergence, air mass, and surface temperature. The results indicate that clouds over this region are very common (occurring about 80% of the time and covering an average of about 60% of the sky), are linked with surface temperature variations (such as being less common and higher during winter cold periods), are poorly correlated with large‐scale factors (such as El Niño), and may be exhibiting some long‐term trends (such as an increase in cloud cover fraction).

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 score0.587
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.029
GPT teacher head0.290
Teacher spread0.261 · 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

Citations13
Published2002
Admission routes2
Has abstractyes

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