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Record W2901119596 · doi:10.1029/2018jc013984

Impact of the Surface Stress on the Volume and Freshwater Transport Through the Canadian Arctic Archipelago From a High‐Resolution Numerical Simulation

2018· article· en· W2901119596 on OpenAlexafffundabout
Nathan Grivault, Xianmin Hu, Paul G. Myers

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsBedford Institute of OceanographyUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsOceanographyArchipelagoGeologyArcticInflowBaySea iceClimatologyWind stressForcing (mathematics)ThroughflowEnvironmental science

Abstract

fetched live from OpenAlex

Abstract We use a numerical model forced with high temporal and spatial resolution atmospheric forcing to evaluate the volume and freshwater transport through the Canadian Arctic Archipelago (CAA). On average, the simulated inflow through the Queen Elizabeth Islands represents 40% of the transport entering the CAA through M'Clure Strait. The transport through Admunsden Gulf represents less than 10% of the total inflow. The impact of sea ice and winds on the volume and freshwater transports into and through this region is also investigated. At Nares Strait and West Lancaster Sound, the transport is overestimated due to too‐mobile sea ice but different physical processes related to surface stress. The ice is driving larger ocean flow in the first case, while causing less flow reduction in the second case. While the transport through the Queen Elizabeth Islands responds to the changes in surface stress over the Beaufort Gyre and northern Baffin Bay, local surface stress opposed to the mean flow over the straits tends to reduce the throughflow transport. In Parry Channel and the southern CAA, the surface stress tends to enhance the transport and have a greater impact locally. Finally, the surface stress related to sea ice motion can significantly change the transport in the CAA during the winter months.

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)0.001
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 score0.222
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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

Citations28
Published2018
Admission routes3
Has abstractyes

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