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Record W1966603643 · doi:10.1175/jcli4268.1

Influence of the Arctic Circumpolar Vortex on the Mass Balance of Canadian High Arctic Glaciers

2007· article· en· W1966603643 on OpenAlexaffabout
Alex Gardner, Martin Sharp

Bibliographic record

VenueJournal of Climate · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolar vortexGlacierArcticClimatologyGlacier mass balanceNorthern HemisphereCircumpolar starAtmospheric sciencesEnvironmental scienceStratosphereGeologyArctic oscillationOceanography

Abstract

fetched live from OpenAlex

Abstract Variability in July mean surface air temperatures from 1963 to 2003 accounted for 62% of the variance in the regional annual glacier mass balance signal for the Canadian High Arctic. A regime shift to more negative regional glacier mass balance occurred between 1986 and 1987, and is linked to a coincident shift from lower to higher mean July air temperatures. Both the interannual changes and the regime shifts in regional glacier mass balance and July air temperatures are related to variations in the position and strength of the July circumpolar vortex. In years when the July vortex is “strong” and its center is located in the Western Hemisphere, positive mass balance anomalies prevail. In contrast, highly negative mass balance anomalies occur when the July circumpolar vortex is either weak or strong without elongation over the Canadian High Arctic, and its center is located in the Eastern Hemisphere. The occurrence of westerly positioned July vortices has decreased by 40% since 1987. The associated shift to a dominantly easterly positioned July vortex was associated with an increased frequency of tropospheric ridging over the Canadian High Arctic, higher surface air temperatures, and more negative regional glacier mass balance.

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 score0.018
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations46
Published2007
Admission routes2
Has abstractyes

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