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Record W1887050604 · doi:10.1029/2010gl043654

Waveform inversion for S‐wave structure in the lowermost mantle beneath the Arctic: Implications for mineralogy and chemical composition

2010· article· en· W1887050604 on OpenAlexaboutno aff
Kenji Kawai, Robert J. Geller, Nobuaki Fuji

Bibliographic record

VenueGeophysical Research Letters · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsGeologyCore–mantle boundaryMantle (geology)GeophysicsArcticTransition zoneShear velocityMineralogyMeteorologyOceanographyPhysics

Abstract

fetched live from OpenAlex

We perform waveform inversion for the radial profile of shear wave velocity in the lowermost mantle beneath the Arctic. We use waveforms from the CANOE (CAnadian NOrthwest Experiment) array, which greatly enhances the resolution in the lowermost mantle as compared to earlier studies. We find a velocity increase at depths from 2500 to 2700 km and a velocity decrease at depths from 2700 km to the core‐mantle boundary (CMB). We interpret the velocity increase as associated with the phase transition from perovskite (pv) to post‐perovskite (ppv), and the velocity decrease as due to a temperature increase in the thermal boundary layer. The shear wave velocity immediately above the core‐mantle boundary (CMB) is 7.11 km/s, while that beneath Central America is 7.25 km/s. This suggests that the proportion of impurities in Mg‐pv or Mg‐ppv beneath the Arctic is 6 mol% larger than that beneath Central America.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.283
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2010
Admission routes1
Has abstractyes

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