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Record W2006305975 · doi:10.1029/2006gl026568

Impact of 3‐D Earth structure on Fennoscandian glacial isostatic adjustment: Implications for space‐geodetic estimates of present‐day crustal deformations

2006· article· en· W2006305975 on OpenAlexaff
Pippa L. Whitehouse, Konstantin Latychev, Glenn A. Milne, J. X. Mitrovica, Roblyn A. Kendall

Bibliographic record

VenueGeophysical Research Letters · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPost-glacial reboundGeologyGeodetic datumLithosphereGeodesyMantle (geology)Glacial periodGeophysicsEarth modelGlobal Positioning SystemSeismologyGeomorphologyTectonics

Abstract

fetched live from OpenAlex

The importance of including lateral Earth structure in the analysis of Fennoscandian glacial isostatic adjustment (GIA) is investigated using a finite volume numerical formulation. Comparing output from radially‐varying 1‐D Earth models and models which account for the presence of plate boundaries, lateral variations in lithospheric thickness and viscosity heterogeneities in the upper and lower mantle, we find that perturbations to present‐day rates of surface deformation due to the inclusion of 3‐D Earth structure significantly exceed current observational uncertainties. Predicted residuals between 1‐D and 3‐D Earth models may be improved with the use of a 1‐D model which approximates the local depth‐dependent mean of the 3‐D model. However, the remaining misfit is still large enough to significantly bias inferences of Earth structure and ice history. We conclude that lateral variations at both global and regional scales must be accounted for when interpreting GPS observations from Fennoscandia.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.026
GPT teacher head0.312
Teacher spread0.286 · 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 designSimulation or modeling
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

Citations58
Published2006
Admission routes1
Has abstractyes

Explore more

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