Generation of zonal flows by ion-temperature-gradient and related modes in the presence of neoclassical viscosity
Bibliographic record
Abstract
Generation of zonal flows by primary waves that are more complex than those considered in the standard drift-wave model is studied. The effects of parallel ion velocity and ion perturbed temperature and the part of the nonlinear mode interaction proportional to the ion pressure are taken into account. This generalization of the standard model allows the analysis of generation of zonal flows by a rather wide variety of primary modes, including ion temperature gradients, ion sound, electron drift, and drift-sound modes. All the listed effects, which are present in the slab geometry model, are complemented by effects of neoclassical viscosity inherent to toroidal geometry. We show that the electrostatic potential of secondary small-scale modes is expressed in terms of a nonlinear shift of the mode frequency and interpret this shift in terms of the perpendicular and parallel Doppler, nonlinear Kelvin-Helmholtz (KH), and nonlinear ion-pressure-gradient effects. A basic assumption of our model is that the primary modes form a nondispersive monochromatic wave packet. The analysis of zonal-flow generation is performed following an approach similar to that of convective-cell theory. Neoclassical zonal-flow instabilities are separated into fast and slow ones, and these are divided into two varieties. The first of them is independent of the nonlinear KH effect, while the second one is sensitive to it.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".