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Record W2065594854 · doi:10.1029/2002jb001786

Lower mantle conductivity anomalies estimated from geomagnetic jerks

2003· article· en· W2065594854 on OpenAlexaff
Hiromichi Nagao, T. Iyemori, Tomoyuki Higuchi, Tohru Araki

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsMira Geoscience (Canada)
Fundersnot available
KeywordsGeologyEarth's magnetic fieldMantle (geology)GeophysicsGeomagnetic secular variationHotspot (geology)GeodesyGeomagnetic stormMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.317
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2003
Admission routes1
Has abstractyes

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