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Record W1967477208 · doi:10.1002/2014jc010353

Landfast ice affects the stability of the <scp>A</scp>rctic halocline: Evidence from a numerical model

2015· article· en· W1967477208 on OpenAlexaboutno aff
Polona Itkin, Martin Lösch, Rüdiger Gerdes

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHaloclineSea iceGeologyArctic ice packFast iceDrift iceArcticOceanographyBathymetryAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract Landfast ice covers large surface areas of the winter Siberian Seas. The immobile landfast ice cover inhibits divergent and convergent motion, hence dynamical sea ice growth and redistribution, decouples winter river plumes in coastal seas from the atmosphere, and positions polynyas at the landfast ice edge offshore. In spite of the potentially large effects, state‐of‐the‐art numerical models usually do not represent landfast ice in its correct extent. A simple parametrization of landfast ice based on bathymetry and internal sea ice strength is introduced and its effects on the simulated Arctic Ocean are demonstrated. The simulations suggest that the Siberian landfast ice impacts the Arctic halocline stability through enhanced brine production in polynyas located closer to the shelf break and by redirecting river water to the Canadian Basin. These processes strengthen the halocline in the Canadian Basin, but erode its stability in the Makarov and Eurasian Basins.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
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 science0.0010.000
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 head0.080
GPT teacher head0.314
Teacher spread0.234 · 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.

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

Citations31
Published2015
Admission routes1
Has abstractyes

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