Investigation of the Differences in Onset Times for Magnetically Conjugate Magnetometers
Bibliographic record
Abstract
We have identified nearly 1,000 onsets using two pairs of hemispheric conjugate ground magnetometers where the onset is defined based on a sharp decline in the H component of the magnetic field at a ground magnetometer station. Specifically, we used the pair of stations at West Antarctica Ice Sheet Divide and Sanikiluaq, Canada; Syowa, Antarctica; and Tjörnes, Iceland. While the onset time in the southern hemisphere is identified by eye, the value of the differences in the onset time between the northern and southern hemispheres is determined using cross covariance. We observe differences in the onset time between the two hemispheres as large as several minutes, but 53% of the events show no difference in the onset time. Using statistics, we show that the largest differences in onset time are associated with the summer and winter seasons and when the IMF By value is limited between 0.5 and 2.5 nT, which is the IMF By range when the local time difference between the northern and southern hemisphere foot points is the smallest. The results indicate that ionospheric conductivity associated with solar illumination plays a role in the differences in onset time between the northern and southern hemisphere when only non-zero differences in onset time are considered. We validate these results with two other less robust methods. The median value of the differences in onset time indicates that the onsets occur ∼23 s earlier in the winter hemisphere than that in the summer hemisphere. It has been reported that the time difference between the start of the substorm in the magnetotail and the observed auroral break up (substorm auroral onset) in the ionosphere is 30 s to 2 min in the current disruption model and the near earth neutral line model, respectively. Our results may be of interest to those two models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".