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Record W2044039881 · doi:10.1175/2009jpo4022.1

The Intrusion Depth of Density Currents Flowing into Stratified Water Bodies

2009· article· en· W2044039881 on OpenAlexaff
Mathew G. Wells, Parthiban Nadarajah

Bibliographic record

VenueJournal of Physical Oceanography · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStratification (seeds)BuoyancyGeostrophic windGeologyScalingWater columnNeutral buoyancyFlux (metallurgy)Entrainment (biomusicology)Gravity currentMechanicsCurrent (fluid)GeophysicsPhysicsGeometryOceanographyInternal waveChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract Theory and laboratory experiments are presented describing the depth at which a density current intrudes into a linearly stratified water column, as a function of the entrainment ratio E, the buoyancy flux in the dense current B, and the magnitude of the stratification N. The main result is that Z ∼ E−1/3B1/3/N. It is shown that the depth of the intrusion scales as Z ∼ (3 ± 1)B1/3/N for laboratory experiments, and as for oceanic density currents. The velocity of a large-scale density current is controlled by a geostrophic balance defined as Ugeo = 0.25g′s/f, where s is the slope and f is the Coriolis parameter. The geostrophic buoyancy flux is then defined by Bgeo = g′Ugeoh, with g′ the reduced gravity and h the thickness of the current. The scaling herein implies that the depth of an oceanic intrusion is relatively insensitive to changes in source water properties but is very sensitive to changes in the stratification of the water column, consistent with the previous scaling of Price and Baringer. For example, if the buoyancy flux of a dense current were to double while the stratification remained constant, then there would only be a 25% increase in the intrusion depth, whereas doubling the stratification would result in a 50% decrease of the intrusion depth.

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 score0.405
Threshold uncertainty score0.295

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 head0.008
GPT teacher head0.224
Teacher spread0.217 · 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

Citations35
Published2009
Admission routes1
Has abstractyes

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