Magnetic turbulent spectra in the magnetosheath: new insights
Bibliographic record
Abstract
Abstract. The spectrum of the magnetic fluctuations measured by the Cluster satellites in the inner magnetosheath is investigated using the k-filtering technique. On a case study, it is shown first that the wave vectors calculated from the Flux Gate Magnetometer (FGM) data fit well with those determined from the Spatio-Temporal Analysis of Field Fluctuations (STAFF) data for their common range of frequency, which allows one to confirm that the high pass filter applied to STAFF data does not alter the spatial characteristics of its spectra. Both analyses confirm the dominance of the mirror mode for frequencies up to 1.4Hz. Furthermore, by comparing the experimental charateristics of the identified mirror mode to the prediction of the linear theory, it is shown that the predicted maximum growth rate is observed in the frequency range 0-0.15Hz, i.e. the FGM range. All the rest of the mirror mode, identified for higher frequencies is more likely to be a non linear extension of the most instable one. This cascade on the spatial scales is, in turn, observed in the satellite frame as a temporal spread due to Doppler shift. Further implications on the real nature of the observed spectrum are discussed.
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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 | 0.001 | 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) | 0.001 | 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".