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Record W4395002395 · doi:10.1029/2024gl108457

The Irminger Gyre as a Key Driver of the Subpolar North Atlantic Overturning

2024· article· en· W4395002395 on OpenAlexaboutno aff
Alejandra Sanchez‐Franks, N. Penny Holliday, Dafydd Gwyn Evans, Nora Fried, Oliver John Tooth, Léon Chafik, Yao Fu, Feili Li, M. Femke de Jong, H. L. Johnson

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsOcean gyreOceanographyThermohaline circulationKey (lock)GeologyClimatologyEnvironmental scienceFisheryBiologySubtropicsEcology

Abstract

fetched live from OpenAlex

Abstract The lower limb of the Atlantic meridional overturning circulation (AMOC) is the equatorward flow of dense waters formed through the cooling and freshening of the poleward‐flowing upper limb. In the subpolar North Atlantic (SPNA), upper limb variability is primarily set by the North Atlantic Current, whereas lower limb variability is less well understood. Using observations from a SPNA mooring array, we show that variability of the AMOC's lower limb is connected to poleward flow in the interior Irminger Sea. We identify this poleward flow as the northward branch of the Irminger Gyre (IG), accounting for 55% of the AMOC's lower limb variability. Over 2014–2018, wind stress curl fluctuations over the Labrador and Irminger Seas drive this IG and AMOC variability. On longer (>annual) timescales, however, an increasing trend in the thickness of intermediate water, from 2014 to 2020, within the Irminger Sea coincides with a decreasing trend in IG strength.

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)0.000
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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