MétaCan
Menu
Back to cohort
Record W2903203454

Decomposition of the Mean Barotropic Transport in a High-Resolution Model of the North Atlantic Ocean

2018· article· en· W2903203454 on OpenAlexaboutno aff
Richard J. Greatbatch, Yuan Wang, Martin Claus, Jinyu Sheng

Bibliographic record

VenueThe EGU General Assembly · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsBarotropic fluidBaroclinityAdvectionGeologyEddyMean flowGulf StreamVorticityFlux (metallurgy)Ocean currentContinental shelfNorth Atlantic Deep WaterPotential vorticityStokes driftMomentum (technical analysis)ClimatologyCurrent meterThermohaline circulationOceanographyMeteorologyTurbulencePhysicsVortex
DOInot available

Abstract

fetched live from OpenAlex

We show how a barotropic shallow water model can be used to decompose the mean barotropic transport from a high-resolution ocean model based on the vertically averaged momentum equations. We apply the method to a high-resolution model of the North Atlantic for which the local vorticity budget is both noisy and dominated by small spatial scales. The shallow water model acts as an effective filter and clearly reveals the transport driven by each term. The potential energy (joint effect of baroclinicity and bottom relief) term is the most important for driving transport, including in the northwest corner, while mean flow advection is important for driving transport along f/H contours around the Labrador Sea continental slope. Both the eddy momentum flux and the mean flow advection terms drive significant transport along the pathway of the Gulf Stream and the North Atlantic Current

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.999

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)0.0000.000

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe EGU General AssemblySame topicOceanographic and Atmospheric ProcessesFrench-language works237,207