MétaCan
Menu
Back to cohort
Record W2042412895 · doi:10.1029/2010jc006803

Modeling the formation and fate of the near‐surface temperature maximum in the Canadian Basin of the Arctic Ocean

2011· article· en· W2042412895 on OpenAlexaboutno aff
Michael Steele, Wendy Ermold, Jinlun Zhang

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersOffice of Polar ProgramsNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsDownwellingCanada BasinOcean gyreMixed layerHaloclineStratification (seeds)ArcticGeologyOceanographyClimatologyEkman transportAdvectionStructural basinSea iceEnvironmental scienceUpwelling

Abstract

fetched live from OpenAlex

A numerical model is used to investigate the time and space extent of the near‐surface temperature maximum (NSTM) of the Canadian Basin of the Arctic Ocean over the years 2000–2009. The NSTM is formed from local summertime absorption of solar radiation which, in some circumstances, descends through the fall and early winter to form a warm subsurface layer just below the winter mixed layer. We find that winter survival of this layer is confined largely to the Beaufort Gyre of the Canadian Basin, where Ekman convergence and downwelling push the summer warm layer down below the winter mixing depth. In recent years, summer stratification has increased, downwelling has accelerated, and the NSTM has warmed as the sea ice cover in the Beaufort Gyre has thinned. The result is a strengthening NSTM which contained enough heat by the end of winter 2007/2008 to melt about 20 cm of sea ice. Northwest of Alaska the model also simulates a second, deeper temperature maximum layer that forms from advection of saltier summer Pacific water. However, this layer is difficult to adequately resolve and maintain given the model's resolution.

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)0.000
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 score0.118
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.029
GPT teacher head0.246
Teacher spread0.218 · 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

Citations75
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research AtmospheresSame topicArctic and Antarctic ice dynamicsFrench-language works237,207