Narrow Width Farley‐Buneman Spectra Above 100 km Altitude
Bibliographic record
Abstract
Abstract For spectra associated with full turbulence the observed mean phase velocity of unstable Farley‐Buneman waves has been found not to exceed the ion‐acoustic speed, cs. This has been attributed to various nonlinear processes. However, weakly turbulent modes are also excited on the edge of the “instability cone.” These modes have to be actual eigenmodes predicted by linear instability theory near‐threshold conditions. Unlike the modes that are associated with strong turbulence, these weakly turbulent modes are affected by the ion drift. This can make the Doppler shift of narrow spectra reach as high as the E × B drift velocity in the upper portion of the unstable layer at small aspect angles. Slow narrow spectra are also predicted nearer the E direction. We have produced a model of the Doppler shift of narrow‐width spectra under various electric field conditions above 100 km altitude. While the fluid dispersion relation is used to clarity the physics, we have also found the eigenmodes from an accepted kinetic dispersion relation. The calculations include a new model of the ion‐acoustic speed based on an empirical model of the electron temperature and of ion frictional heating under strong electric field conditions. The model provides an explanation for various VHF observations of the Doppler shift of narrow spectra that have been called “Type III spectra” and “Type IV spectra” in the existing literature.
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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 | 0.000 |
| 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) | 0.002 | 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".