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Record W2096034816 · doi:10.1029/2003jb002619

Continuous GPS measurements of postglacial adjustment in Fennoscandia: 2. Modeling results

2004· article· en· W2096034816 on OpenAlexaff
Glenn A. Milne, J. X. Mitrovica, Hans‐Georg Scherneck, J. L. Davis, Jan M. Johansson, Hannu Koivula, Martin Vermeer

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPost-glacial reboundGeologyGeodesyGlobal Positioning SystemDeglaciationGlacial periodMantle (geology)GeophysicsGeomorphologyComputer science

Abstract

fetched live from OpenAlex

Data collected under the auspices of the BIFROST GPS project yield a geographically dense suite of estimates of present‐day, three‐dimensional (3‐D) crustal deformation rates in Fennoscandia [ Johansson et al. , 2002 ]. A preliminary forward analysis of these estimates [ Milne et al. , 2001 ] has indicated that models of ongoing glacial isostatic adjustment (GIA) in response to the final deglaciation event of the current ice age are able to provide an excellent fit to the observed 3‐D velocity field. In this study we revisit our previous GIA analysis by considering a more extensive suite of forward calculations and by performing the first formal joint inversion of the BIFROST rate estimates. To establish insight into the physics of the GIA response in the region, we begin by decomposing a forward prediction into the three contributions associated with the ice, ocean, and rotational forcings. From this analysis we demonstrate that recent advances in postglacial sea level theory, in particular the inclusion of rotational effects and improvements in the treatment of the ocean load in the vicinity of an evolving continental margin, involve peak signals that are larger than the observational uncertainties in the BIFROST network. The forward analysis is completed by presenting predictions for a pair of Fennoscandian ice histories and an extensive suite of viscoelastic Earth models. The former indicates that the BIFROST data set provides a powerful discriminant of such histories. The latter yields bounds on the (assumed constant) upper and lower mantle viscosity (ν UM , ν LM ); specifically, we derive a 95% confidence interval of 5 × 10 20 ≤ ν UM ≤ 10 21 Pa s and 5 × 10 21 ≤ ν LM ≤ 5 × 10 22 Pa s, with some preference for (elastic) lithospheric thickness in excess of 100 km. The main goal of the (Bayesian) inverse analysis is to estimate the radial resolving power of the BIFROST GPS data as a function of depth in the mantle. Assuming a reasonably accurate ice history, we demonstrate that this resolving power varies from ∼200 km near the base of the upper mantle to ∼700 km in the top portion of the lower mantle. We conclude that the BIFROST data are able to resolve structure on radial length scale significantly smaller than a single upper mantle layer. However, these data provide little constraint on viscosity in the bottom half of the mantle. Finally, elements of both the forward and inverse analyses indicate that radial and horizontal velocity estimates provide distinct constraints on mantle viscosity.

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)0.001
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 score0.344
Threshold uncertainty score0.684

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
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 head0.056
GPT teacher head0.305
Teacher spread0.249 · 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

Citations268
Published2004
Admission routes1
Has abstractyes

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