MétaCan
Menu
Back to cohort
Record W2073700961 · doi:10.1029/2004gl021454

Influence of lithospheric thickness variations on 3‐D crustal velocities due to glacial isostatic adjustment

2005· article· en· W2073700961 on OpenAlexafffund
Konstantin Latychev, J. X. Mitrovica, M. E. Tamisiea, Jeroen Tromp, R. Moucha

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAdolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California BerkeleyNational Aeronautics and Space Administration
KeywordsLithosphereGeologyPost-glacial reboundGeodetic datumDiscontinuity (linguistics)RidgeGeodesyPlate tectonicsTectonicsSeismologyGlacial periodGeophysicsGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Predictions of 3‐D crustal velocities driven by glacial isostatic adjustment (GIA) have generally been based on spherically symmetric Earth models. We adopt a finite‐volume formulation to explore the impact of lateral variations in elastic plate strength, including lithospheric thickness changes across the continent‐ocean interface and plate boundary weak zones, on these predictions. Weak zones introduce horizontal rate perturbations with a plate scale coherency and amplitudes reaching 1–2 mm/yr; radial velocity perturbations can be as large, but are geographically isolated to the weak zones (specifically, the North Atlantic Ridge). A discontinuity in ocean‐continent lithospheric thickness significantly impacts rates along continental margins (order 1 mm/yr for radial rates and generally about half this for tangential rates). We conclude that lateral variations in lithospheric strength should be included in future GIA analyzes of space‐geodetic survey results and in assessing the impact of GIA on the stability of geodetic reference frames.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.286
Teacher spread0.261 · 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.

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

Citations51
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicearthquake and tectonic studiesFrench-language works237,207