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Record W2895320187 · doi:10.1029/2018jc014080

The Impact of Tides on Simulated Landfast Ice in a Pan‐Arctic Ice‐Ocean Model

2018· article· en· W2895320187 on OpenAlexaff
Jean‐François Lemieux, Lei Ji, Frédéric Dupont, François Roy, Martin Lösch, Camille Lique, Frédéric Laliberté

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsGeologySea iceIce shelfArctic ice packAntarctic sea iceDrift iceIcebergOceanographyArcticForcing (mathematics)CryosphereClimatology

Abstract

fetched live from OpenAlex

Abstract The impact of tides on the simulated landfast ice cover is investigated. Pan‐Arctic simulations are conducted with an ice‐ocean (CICE‐NEMO) model with a modified rheology and a grounding scheme. The reference experiment (without tides) indicates there is an overestimation of the extent of landfast ice in regions of strong tides such as the Gulf of Boothia, Prince Regent Inlet, and Lancaster Sound. The addition of tides in the simulation clearly leads to a decrease of the extent of landfast ice in some tidally active regions. This numerical experiment with tides is more in line with observations of landfast ice in all the regions studied. Thermodynamics and changes in grounding cannot explain the lower landfast ice area when tidal forcing is included. We rather demonstrate that this decrease in the landfast ice extent is dynamically driven by the increase of the ocean‐ice stress due to the tides.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.342
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 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

Citations36
Published2018
Admission routes1
Has abstractyes

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