Effects of cold electron number density variation on whistler-mode wave growth
Bibliographic record
Abstract
We examine how the growth of magnetospheric whistler-mode waves depends on the cold (background) electron number density N-0. The analysis is carried out by varying the cold-plasma parameter a = (electron gyrofrequency)(2)/(electron plasma frequency) 2 which is proportional to 1/N-0. For given values of the thermal anisotropy A(T) and the ratio N-h/N-0, where N-h is the hot (energetic) electron number density, we find that, as N-0 decreases, the maximum values of the linear and nonlinear growth rates decrease and the threshold wave amplitude for nonlinear growth increases. Generally, as N-0 decreases, the region of (N-h/N-0, A(T))-parameter space in which nonlinear wave growth can occur becomes more limited; that is, as N-0 decreases, the parameter region permitting nonlinear wave growth shifts to the top right of (N-h/N-0, A(T)) space characterized by larger N-h/N-0 values and larger A(T) values. The results have implications for choosing input parameters for full-scale particle simulations and also in the analysis of whistler-mode chorus data.
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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".