Bibliographic record
Abstract
Abstract The present study investigates the linear properties of the current sheet shear instability (CSSI) based on the two‐fluid equations. The mode is typically excited in the thin current layer formed around the X line during a quasi‐steady phase of collisionless reconnection and is considered to give rise to the anomalous momentum transport. The linear analyses are carried out for a realistic current sheet as evolved in collisionless reconnection, where the current density profile is produced by the nonuniform ion and electron flows and the pressure balance is maintained due to the temperature gradients. The density profile is assumed to be uniform, so that the lower hybrid drift instability is mostly suppressed. We confirm that the eigenfunctions in the numerical analysis are well consistent with the profiles in a kinetic simulation, implying that the two‐fluid approximation is valid for the CSSI. The mass ratio dependencies of the wave number and growth rate are remarkable for the electron‐scale current sheet, indicating that both the electrons and ions contribute to the wave generation. From the analytical analysis, it is found that these mass ratio dependencies originate from the fact that the ion momentum balance is coupled with the electron dynamics in the electron‐scale current layer. In particular, the electron inertia and electron flow shear play a significant role in generating the CSSI through the induction electric and magnetic fields.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".