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Record W2108501651 · doi:10.1175/jpo2713.1

Stirring by Small-Scale Vortices Caused by Patchy Mixing

2005· article· en· W2108501651 on OpenAlexaff
Miles A. Sundermeyer, James R. Ledwell, Neil S. Oakey, B. J. W. Greenan

Bibliographic record

VenueJournal of Physical Oceanography · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsBedford Institute of Oceanography
FundersOffice of Naval Research
KeywordsDispersion (optics)Mixing (physics)TurbulenceMechanicsGeologyGeostrophic windScalingRADIUSLength scaleVortexMomentum (technical analysis)PlumeMagnitude (astronomy)Thermal diffusivityAtmospheric sciencesMeteorologyGeometryPhysicsOpticsThermodynamics

Abstract

fetched live from OpenAlex

Abstract Evidence is presented that lateral dispersion on scales of 1–10 km in the stratified waters of the continental shelf may be significantly enhanced by stirring by small-scale geostrophic motions caused by patches of mixed fluid adjusting in the aftermath of diapycnal mixing events. Dye-release experiments conducted during the recent Coastal Mixing and Optics (CMO) experiment provide estimates of diapycnal and lateral dispersion. Microstructure observations made during these experiments showed patchy turbulence on vertical scales of 1–10 m and horizontal scales of a few hundred meters to a few kilometers. Momentum scaling and a simple random walk formulation were used to estimate the effective lateral dispersion caused by motions resulting from lateral adjustment following episodic mixing events. It is predicted that lateral dispersion is largest when the scale of mixed patches is on the order of the internal Rossby radius of deformation, which seems to have been the case for CMO. For parameter values relevant to CMO, lower-bound estimates of the effective lateral diffusivity by this mechanism ranged from 0.1 to 1 m2 s−1. Revised estimates after accounting for the possibility of long-lived motions were an order of magnitude larger and ranged from 1 to 10 m2 s−1. The predicted dispersion is large enough to explain the observed lateral dispersion in all four CMO dye-release experiments examined.

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 score0.362
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations37
Published2005
Admission routes1
Has abstractyes

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