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Record W4317621286 · doi:10.3390/jmse11020254

Regional and Remote Influence on the Sea Ice in the Kara Sea

2023· article· en· W4317621286 on OpenAlexfundno aff
U. V. Prokhorova, Г. В. Алексеев, A. E. Vyazilova

Bibliographic record

VenueJournal of Marine Science and Engineering · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersRussian Science FoundationAlberta Agricultural Research Institute
KeywordsSea iceClimatologyOceanographyAntarctic sea iceSea surface temperatureArctic ice packGeologyEnvironmental science

Abstract

fetched live from OpenAlex

This article examines the relationship between interannual changes in the sea ice extent and thickness in the Kara Sea with climate change in the region and with sea surface temperature in the tropical North Atlantic. The data from observations at meteorological stations, ERA5 reanalysis, and data on the sea ice from the AARI website for 1979–2021 were used. The growth of ice in winter is most influenced by air temperature and downward long-wave radiation. In summer, interannual changes in sea ice extent are closely related to air temperature. The remote influence of the sea surface temperature anomalies in the tropics of the North Atlantic on the summer (July–September) sea ice in the Kara Sea is discovered 33–35 months later. A significant correlation between climate and sea ice anomalies can serve as the basis for predicting up to four years ahead.

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)0.000
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 score0.143
Threshold uncertainty score0.121

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.011
GPT teacher head0.202
Teacher spread0.190 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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