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Record W1989142635 · doi:10.1063/1.1287652

Conjugate flows for a three-layer fluid

2000· article· en· W1989142635 on OpenAlexafffund
Kevin G. Lamb

Bibliographic record

VenuePhysics of Fluids · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConjugatePhysicsStratified flowPycnoclineThin layerMode (computer interface)Flow (mathematics)MechanicsLayer (electronics)Mathematical analysisMathematicsTurbulenceGeologyMaterials science

Abstract

fetched live from OpenAlex

A method for computing conjugate flows for a non-Boussinesq, three-layer fluid with arbitrary constant currents is developed. The general solution for a two-layer fluid is obtained as a special case. Symmetric stratifications at rest, with the upper and lower layer depths equal to h and identical density jumps across each interface, are considered in detail using the Boussinesq approximation. Mode-1 conjugate flows exist for h hc2>hc1 two additional asymmetric solutions exist. Comparisons with solutions for continuous stratifications with thin pycnoclines are made. Mode-2 solutions are more sensitive to the width of the pycnocline than are mode-1 solutions. Comparisons between three-layer non-Boussinesq and Boussinesq solutions are also made. For a total density variation of 4% of the mean value the two solutions are similar. For larger density variations the mode-2 solutions can be significantly different.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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 designSimulation or modeling
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
Published2000
Admission routes2
Has abstractyes

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