Bibliographic record
Abstract
Summary form only given, as follows. The advent of high-performance scientific computing in the last few decades has given researchers a valuable tool for understanding turbulent transport in fluids and in plasmas. However, despite the efficiency of the pseudospectral method, the direct evaluation of statistical moments of the Navier-Stokes equation by numerical simulation of high-Reynolds number turbulence is not yet possible, even in two dimensions. The effort spent resolving the dissipation scales dominates the computation, even though it is often the dynamics of the large energy-containing scales that are of greater physical interest. We use these natural constraints of two-dimensional turbulence to develop more reliable subgrid models in which the ratio of the upscale and downscale transfer depend only on the wavenumbers and not on the energies of the deleted dissipation modes. We also consider a flux extrapolation scheme, where the subgrid model is constrained to remove a wavenumber-independent amount of energy flux from the small scales, after compensating for the effects of dissipation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".