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Record W4414458168 · doi:10.1038/s41612-025-01099-5

Summer sea ice in the Northwestern Chukchi Sea observed in 2024 for the first time in 25 years

2025· article· en· W4414458168 on OpenAlexafffund
G. W. K. Moore, Jinlun Zhang, Axel Schweiger, Michael Steele, Thomas J. Ballinger

Bibliographic record

Venuenpj Climate and Atmospheric Science · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaOffice of Naval ResearchNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsSea iceArctic ice packAntarctic sea iceDrift iceArctic sea ice declineCryosphereSea ice thickness

Abstract

fetched live from OpenAlex

The Arctic Ocean has seen a profound sea ice loss during the summer, with changes most pronounced in the Western Arctic. This has resulted in the Chukchi Sea, located just north of Bering Strait, being ice-free by the end of summer, i.e. September, since 2000, except during 2024. Here using the ice thickness budget, we investigate the processes responsible for the return of summer sea ice to the region during 2024. We show that an exceptional ice convergence event in February 2024, along with additional events in the winter and spring, resulted in ice thicknesses along the Siberian coast of the Chukchi Sea through the summer months that exceeded values last seen in the region during the late 20 th century. The reduced penetration of shortwave radiation through the anomalously thick ice contributed to a delay in melt, contributing to the presence of sea ice in the region during the summer of 2024. We also argue that a thinner and more mobile ice pack contributed to this remarkable return of summer sea ice after a 25-year hiatus, opening the possibility of similar events in the future.

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 score0.091
Threshold uncertainty score0.181

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)0.0010.000

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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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