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Record W2098228575 · doi:10.1175/jpo3050.1

Interpreting Eddy Fluxes

2007· article· en· W2098228575 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Physical Oceanography · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsEddy diffusionStatistical physicsTurbulenceBuoyancyEulerian pathDiabaticMechanicsIsopycnalMesoscale meteorologyAdiabatic processPhysicsMeteorologyGeologyMathematicsClimatologyThermodynamicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract A generalization of the transformed Eulerian and temporal residual means is presented. The new formulation uses rotational fluxes of buoyancy, and the full hierarchy of statistical density moments, to reduce the cross-isopycnal eddy flux to the physically relevant component associated with the averaged water mass properties. The resulting eddy-induced diapycnal diffusivity vanishes for adiabatic, statistically steady flow, and is related to either the growth or decay of mesoscale density variance and/or the covariance between small-scale forcing (mixing) and density fluctuations, such as that associated with the irreversible removal of density variance by dissipation. The relationship between the new formulation and previous approaches is described and is illustrated using results from an eddying channel model. The formalism is quite general and applies to all kinds of averaging and to any tracer (not just density).

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.

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)0.001
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 score0.098
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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