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Record W2038595833 · doi:10.1029/2007jc004553

Spatial and temporal variability of sea ice in the southern Beaufort Sea and Amundsen Gulf: 1980–2004

2008· article· en· W2038595833 on OpenAlexafffundabout
R. J. Galley, Erica Key, David G. Barber, Byongjun Hwang, Jens K. Ehn

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
FundersArcticNet
KeywordsSea iceOceanographyArctic ice packAntarctic sea iceArctic sea ice declineDrift iceFast iceGeologyArcticClimatologyCryosphere

Abstract

fetched live from OpenAlex

Changing extent, location, and motion of the Arctic perennial pack affect the annual evolution of seasonal ice zones. Canadian Ice Service digital ice charts covering the southern Beaufort Sea and Amundsen Gulf are used to illustrate summer and winter conditions and trends between 1980 and 2004 for several sea ice stages of development. Results illustrate average sea ice conditions within the region in summer and winter for predominant sea ice types and changes in the relative concentration of sea ice types in summer and winter. In summer, a trend toward increased old sea ice concentration occurred near the mouth of Amundsen Gulf, with a trend toward decreasing summer first‐year sea ice farther west. In winter, increasing thick first‐year sea ice extent appears to be replacing young sea ice within the flaw lead system in the region. The dynamically driven breakup of sea ice in spring in the Amundsen Gulf is a highly variable event taking anywhere between 2 and 22 weeks to completely remove ice from the gulf. The timing and duration of the open water season depends upon the extent and timing of old ice influx. Freezeup occurs very quickly, proceeding from west to east with little temporal variability. The results of this paper are used to set the context for the Canadian Arctic Shelf Exchange Study (CASES) in terms of sea ice dynamic and thermodynamic processes.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.033
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.269
Teacher spread0.246 · 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

Citations93
Published2008
Admission routes3
Has abstractyes

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