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Record W6977452972 · doi:10.6084/m9.figshare.c.6823321

Supplementary material from "Buoyancy forcing and the subpolar Atlantic meridional overturning circulation"

2023· other· en· W6977452972 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsOcean gyreWater massForcing (mathematics)North Atlantic Deep WaterSubtropicsConvectionPrecipitationThermohaline circulationBoundary current

Abstract

fetched live from OpenAlex

The North Atlantic meridional overturning circulation and its variability are examined in terms of the overturning in density space and diapycnal water mass transformation. The magnitude of the mean overturning is similar to the surface water mass transformation, but the density and properties of these waters are modified by diapycnal mixing. Surface waters are progressively densified while circulating cyclonically around the subpolar gyre, with the densest waters and deepest convection occurring in the Labrador Sea and Nordic Seas. The eddy-driven interaction between the convective interior and boundary currents is a key to the export of dense waters from marginal seas. Due to the multitude of pathways of dense waters within the subpolar gyre, as well as mixing with older waters, waters exiting the subpolar gyre have a wide range of ages, with a mean age on the order of a decade. As a result, interannual changes in water mass transformation are mostly balanced locally and do not result in changes in export to the subtropics. Only persistent changes in water mass transformation result in changes in export to the subtropics. The dilution of signals from upstream water mass transformation suggests that variability in export of dense waters to the subtropics may be controlled by other processes, including interaction of dense waters with the energetic upper ocean.This article is part of the theme issue ‘Atlantic overturning: new observations and challenges’.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.7900.007

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 head0.252
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2023
Admission routes1
Has abstractyes

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