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Record W2981274654 · doi:10.48550/arxiv.1808.09131

Ensemble algorithm for parametrized flow problems with energy stable\n open boundary conditions

2018· article· en· W2981274654 on OpenAlexafffund
Aziz Takhirov, Jiajia Waters

Bibliographic record

VenuearXiv (Cornell University) · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStability (learning theory)Forcing (mathematics)Boundary (topology)MathematicsBoundary value problemFlow (mathematics)ViscosityEnergy (signal processing)Applied mathematicsOpen setPeriodic boundary conditionsMathematics Subject ClassificationMathematical analysisComputer sciencePhysicsGeometryDiscrete mathematicsThermodynamics

Abstract

fetched live from OpenAlex

We propose novel ensemble calculation methods for Navier-Stokes equations\nsubject to various initial conditions, forcing terms and viscosity\ncoefficients. We establish the stability of the schemes under a CFL condition\ninvolving velocity fluctuations. Similar to related works, the schemes require\nsolution of a single system with multiple right-hand sides. Moreover, we extend\nthe ensemble calculation method to problems with open boundary conditions, with\nprovable energy stability.\n

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 categoriesInsufficient payload (model declined to judge)
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 score0.734
Threshold uncertainty score0.998

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.074
GPT teacher head0.196
Teacher spread0.122 · 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.

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

Citations12
Published2018
Admission routes2
Has abstractyes

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