Simulation of transport in the FT-2 tokamak up to the electron scale with GENE
Bibliographic record
Abstract
Abstract Prior experimental work on the FT-2 tokamak has observed electron density fluctuations at electron Larmor radius scales using the enhanced scattering (ES) diagnostic (Gusakov et al 2006 Plasma Phys. Control. Fusion 48 A371–6, Gurchenko and Gusakov 2010 Plasma Phys. Control. Fusion 52 124035). Gyrokinetic GENE simulations of conditions at the upper hybrid resonance layer probed by the ES diagnostic show the presence of the anticipated turbulence from the electron temperature gradient (ETG) driven instability in linear and nonlinear simulations. Ion-scale turbulence is responsible for majority of the transport via trapped electron modes, while impurities act to merge the spectrum of the ion and the electron scale instabilities into a continuum. The linear spectrum at electron scales is characterized by maximal growth rate at a significant ballooning angle θ 0, and at ion scales the turbulence is broad in the ballooning angle distribution. The neoclassical shearing rate obtained from GENE breaks symmetry in nonlinear simulations of ETG turbulence, which manifests itself as an asymmetric turbulence spectrum. The electron density fluctuation spectrum obtained with GENE corresponds well to the ES measurement at electron scales, as do the fluxes obtained from the ion-scale simulations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".