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Record W2015450093 · doi:10.3137/ao.460402

Mixing in downslope flows in the ocean ‐ plumes versus gravity currents

2008· article· en· W2015450093 on OpenAlexvenueno aff
Peter G. Baines

Bibliographic record

VenueATMOSPHERE-OCEAN · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsGravity currentMixing (physics)GeologyOceanographyCurrent (fluid)MechanicsGeophysicsPhysicsInternal wave

Abstract

fetched live from OpenAlex

ABSTRACT The nature of downslope flows into stratified environments as revealed by laboratory experiments is described, and the results are then applied to interpret particular downslope flows into the ocean. In the labora-tory, non-rotating downslope flows can be divided into two main types: detraining gravity currents over suffi-ciently gentle slopes, where the buoyancy force of the dense downflow is mainly balanced by bottom drag, and entraining plumes over sufficiently steep slopes, where the buoyancy force is balanced by vigorous entrainment of environmental fluid from above. This mixing character of the flow is determined by the bottom slope, the drag coefficient and the buoyancy number B = QN3/G2, where Q and G are the volume flux and buoyancy of the down-flow and N is the buoyancy frequency of the environment. These experiments may be applied to situations in the ocean where the flow is in approximate geostrophic balance with its transverse pressure gradient, and the para-meters are applied to the flow path on the slope. Examples are provided for a number of downslope flows in var-ious locations, including the Red Sea outflow, the Mediterranean outflow into the Black Sea and the Atlantic, the Denmark Strait overflow and the outflow from the Ross Sea. RÉSUMÉ [Traduit par la rédaction] Nous décrivons la nature des écoulements descendants dans les environnements stratifiés en nous basant sur des expériences en laboratoire et nous nous servons ensuite des résultats pour interpréter certains écoulements descendants dans l’océan. Au laboratoire, on peut regrouper les

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2008
Admission routes1
Has abstractyes

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