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Record W4200158958 · doi:10.1029/2021jc018024

Sea Ice Dynamics in Hudson Strait and Its Impact on Winter Shipping Operations

2021· article· en· W4200158958 on OpenAlexafffundabout
David G. Babb, Sergei Kirillov, R. J. Galley, Fiammetta Straneo, Jens K. Ehn, Stephen Howell, Mike Brady, Natasha A. Ridenour, David G. Barber

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of AlbertaEnvironment and Climate Change CanadaFisheries and Oceans CanadaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Meteorological and Oceanographic SocietyManitoba HydroNational Science Foundation
KeywordsSea iceArctic ice packOceanographyGeologyDrift iceAntarctic sea iceFast iceArcticClimatologyLead (geology)Ice shelfCryosphereGeomorphology

Abstract

fetched live from OpenAlex

Abstract Hudson Strait is seasonally ice covered and is the only part of the Canadian Arctic where winter shipping takes place. Yet, very little is known about the thickness and dynamics of this ice pack. During winter operations, icebreakers often face besetting events, which can slow or immobilize vessels for up to a few days. Using in situ observations of ice draft and drift collected by moored sonars at two sites in Hudson Strait from 2005 to 2009, we provide the first detailed analysis of sea ice dynamics within Hudson Strait and provide insights into the processes that dictate ice thickness and internal pressure along this unique winter shipping corridor. Prevailing northwesterly winds drive south‐southeastward ice motion within the Strait, maintaining polynyas along Baffin Island on the north side of the Strait, and compressing the ice pack against Nunavik on the southern side. As a result, ice on the northern side remains young and thin throughout winter ( = 1.25 m), whereas ice on the southern side is older, heavily deformed and ∼60% thicker by March ( = 2.01 m). Intermittent reversals to southeasterly winds decompress the ice pack on the southern side, increasing the presence of leads and easing navigation through the ice pack to the port in Deception Bay. The spatial variability in sea ice thickness elucidated by the moorings is corroborated at the regional scale using satellite observations from ICESat‐2 during winter 2019, 2020, and 2021, and complimented by high‐resolution fields of sea ice motion during winter 2021.

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)0.001
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 score0.405
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.032
GPT teacher head0.335
Teacher spread0.304 · 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

Citations17
Published2021
Admission routes3
Has abstractyes

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