Lower mantle conductivity anomalies estimated from geomagnetic jerks
Bibliographic record
Abstract
The occurrence epochs and duration periods of the 1969, 1978, and 1991 geomagnetic jerks are estimated for 65 geomagnetic observatories by applying a statistical time series model to monthly means of the geomagnetic eastward component. It is found for every jerk that the occurrence epochs around South Africa and South Pacific Ocean are delayed several years from those in other regions. Moreover, it is found for the 1969 and 1978 jerks that the duration times around South Africa, which are defined as the lengths of the duration periods, are longer than those in other regions. The distribution of these anomalous regions of the jerks (i.e., South Africa and South Pacific Ocean) may imply the existence of higher conductivities in the lower mantle beneath these regions, which possibly relates to the fact that the velocity of a seismic S wave in the D″ layer beneath these regions is slower than that in other regions. The mantle conductivities beneath South Africa, South Pacific Ocean, and other regions are estimated through a numerical simulation; the magnetic diffusion equation in the mantle is solved for an abrupt magnetic change generated at the core‐mantle boundary. Comparing the results obtained by the simulation with those obtained by the data analysis, it is plausible that the mantle conductivities beneath South Africa and South Pacific Ocean are higher than that beneath other regions, although there is an ambiguity in the estimated magnitudes of the mantle conductivity.
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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 | 0.001 |
| 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 | 0.000 |
| 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".