Paleomagnetic field properties at high southern latitude
Bibliographic record
Abstract
Statistical analyses of paleomagnetic data from lava flows are used to study geomagnetic field behavior on million year timescales. Previous paleomagnetic studies have lacked high‐latitude measurements necessary to investigate the persistence of geomagnetic anomalies observed in the recent and historical field and replicated in some numerical geodynamo simulations. These simulations suggest that reduced convective flow inside the tangent cylinder may affect the magnetic field at high latitude, whereas lower‐latitude observations are expressions of columnar/helical flow outside the tangent cylinder. This paper presents new paleointensity and paleodirectional data from 100 volcanic sites in the Erebus Volcanic Province (EVP), Antarctica, and 21 new age determinations by the 40Ar/39Ar incremental heating method. The new EVP data are combined with previously published paleomagnetic and geochronological results, providing 133 sites, 91 having radioisotopic dates. Modified Thellier‐Thellier paleointensity estimates are reported for 47 sites (37 have dates). Ages for the combined data set span 0.03 to 13.42 Ma. The 125 high‐quality EVP directional data selected from the merged data set have a non‐Fisherian distribution and a mean direction with an inclination anomaly of ∼3°, but 95% confidence limits include the prediction from a geocentric axial dipole. Virtual geomagnetic pole (VGP) dispersions for Brunhes, Matuyama, and the combined 0–5 Ma data set are consistently high compared with values from middle‐ to low‐latitude regions regardless of the criterion used to determine transitional fields. With VGP latitude cut off at 45°, the dispersion (23.9 ± 2.1°) for the combined 0–5 Ma EVP data set is consistent with earlier high‐latitude data and paleosecular variation (PSV) in Model G but not with some more recent statistical PSV models. Mean EVP paleointensity of 31.5 ± 2.4 μT, derived from 41 high‐quality sites, is about half the current value at McMurdo (∼63 μT). The result is essentially independent of data selection criteria. High VGP dispersion and low‐intensity values support the global observation of anticorrelation between directional variability and field strength. Simulations of time‐varying dipole strength show that uneven temporal sampling may bias the mean EVP intensity estimate, but the possibility of persistently anomalous field behavior at high latitude cannot be excluded.
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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 | 0.000 | 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".