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Record W2090148369 · doi:10.1029/2001jd900060

Trends in sea level pressure across western Canada

2001· article· en· W2090148369 on OpenAlexaboutno aff
Lawrence C. Nkemdirim, Dagmar Budikova

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsArcticClimatologyEnvironmental scienceSea levelTrend analysisGeographyThe arcticPhysical geographyOceanographyGeologyMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper examines recent trends in sea level pressure (SLP) in western Canada. Time series of mean monthly SLP from each of 51 stations from 1956 to 1993 were analyzed for temporal and spatial trends using a number of analytical techniques, such as simple regression and correlation, trend surface analyzes, and geographical information system. Over the period, annual SLP declined at an average rate of 0.4 hPa/100 yr. Seasonal trends were clearly marked. In winter (December, January, February) and spring (March, April, May), SLP decreased at an average rate of 1.6 hPa/100 yr and 3.3 hPa/100 yr, respectively. The opposite trend was measured in the summer (+1.1 hPa/100 yr) and the fall (+2.3 hPa/100 yr). Trends in January and March were strongly negative (−9.7 hPa/100 yr and −4.3 hPa/100 yr, respectively). Equivalent values for July and October were +0.30 hPa/100 yr and +5.9 hPa/100 yr, respectively. All trends and their statistical significance levels amplified poleward. In general, trends were larger and more consistent in the Arctic and sub‐Arctic, and least in British Columbia and the southern prairies. These observations suggest a weakening of the Arctic High in the winter and spring which, if correct, is in agreement with recent mild winters in the Canadian Prairies and the Arctic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.118
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.334
Teacher spread0.251 · 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 teacher head, 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

Citations5
Published2001
Admission routes1
Has abstractyes

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