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Record W4288766332 · doi:10.26443/msurj.v17i1.172

Coastal Sea-Ice Break-Up Events in Beringia

2022· article· en· W4288766332 on OpenAlexafffund
Samuel Aucoin, Bruno Tremblay, R. Newton

Bibliographic record

VenueMcGill Science Undergraduate Research Journal · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaEuropean CommissionNational Oceanic and Atmospheric AdministrationUniversities Space Research AssociationNational Science Foundation
KeywordsSea iceDrift iceArctic sea ice declineClimatologyArcticArctic ice packGeologyEnvironmental scienceAntarctic sea iceIce-albedo feedbackOceanography

Abstract

fetched live from OpenAlex

We quantify changes in break‐up events of landfast ice in the transition from a perennial to a seasonal sea ice cover in the Arctic. A break‐up event is defined as a time when coastal sea ice concentration drops below 95% after a minimum period of 10 days of stable ice conditions. To this end we analyze output diagnostics from the Community Earth System Model (Version 1) – Large Ensemble from 1920 to 2080, focusing on six coastal communities of Alaska, Chukotka, and the Kamtchatka Peninsula: Utqiaġvik, Point Hope, Gambell, Novoye Chaplino, Sireniki, and Pakhachi. Model results generally agree with the satellite record with open water formation along the coastline associated with sustained offshore winds, although the sensitivity of CESM1‐LE is higher than that of observations due to the absence of a landfast ice parameterization in CESM1‐ LE. Specifically, we see a linear relationship between the magnitude of the opening and offshore surface wind stresses integrated over the 10 days prior to the opening event, (p‐value < 0.01). While the break‐up event frequency increases (5.53 × 10−5 events/day/year for Utqiagvik) in the 21st century due to the thin- ning, or weakening, of the landfast ice cover, the total number of winter break‐up events decreases due to a shortening of the winter season (mean of ‐5.3 days/decade).

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.040
GPT teacher head0.308
Teacher spread0.268 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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