Sheath and presheath in a collisionless plasma containing negative ions with an open magnetic field
Bibliographic record
Abstract
The effects of an axisymmetric magnetic mirror field with diverging field lines on the plasma presheath and sheath are numerically investigated by solving the plasma–sheath equation for a collisionless plasma in the presence of negative ions. The positive and negative ions with a finite temperature are generated throughout the volume where the sources vary according to the ionization rate. Electrons are assumed to obey the Boltzmann relation. The sheath formation and Debye shielding, which depends considerably on the magnetic strength profile, decrease remarkably on applying an expanding magnetic field. The dependence of the particle densities and the electrostatic potential on the magnetic field profiles are explicitly investigated in this study. Negative ions with sufficient energy penetrate into the sheath following the field lines and eventually reflect back at a point where the mirror force and the electrostatic force balance each other.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".