Ground magnetometer observation of a cross‐phase reversal at a steep plasmapause
Bibliographic record
Abstract
The cross‐phase technique employs ground‐based magnetometer data in order to determine the resonance frequency of a geomagnetic field line. Typically, a positive cross‐phase maximum identifies the field line resonance frequency, but occasionally, a negative cross‐phase maximum is observed and is believed to be a feature of the steep density gradient at the plasmapause. For a few hours during the local morning of 14 May 2001 the cross‐phase maximum, observed using two pairs of ground‐based magnetometer stations from the European sector, with midpoints at L = 3.16 and L = 3.34, reversed polarity from positive to negative. All other British Geological Survey, Sub‐Auroral Magnetometer Network, and International Monitor for Auroral Geomagnetic Effects (IMAGE) magnetometer array station pairs examined between L = 2.39 and L = 6.54 showed a positive cross‐phase maximum throughout the day. The Imager for Magnetopause‐to‐Aurora Global Exploration (IMAGE) satellite made an excellent close magnetic conjunction with these ground‐based magnetometer arrays on this day, and data from the IMAGE Radio Plasma Imager instrument show a very steep plasmapause in this region during this UT interval. IMAGE Extreme Ultraviolet Imager global plasmasphere images show that the plasmapause moved outward through the day, passing through the region of the observed negative cross‐phase maxima. This rare observation of a negative cross‐phase maximum occurs at the location of a plasmapause with a gradient steeper than r−8 and thus is in agreement with theory. The two cross‐phase peak polarity reversals are explained by the evolution of the local density profile.
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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".