Glacial isostatic adjustment of the British Isles: new constraints from GPS measurements of crustal motion
Bibliographic record
Abstract
We compared estimates of crustal velocities within Great Britain based on continuous global positioning system (CGPS) measurements to predictions from a model of glacial isostatic adjustment (GIA). The observed and predicted values for vertical motion are highly correlated indicating that GIA is the dominant geodynamic process contributing to this field. In contrast, motion of the Eurasian plate dominates the horizontal motion component. A model of plate motion was adopted to remove this signal in order to estimate intraplate horizontal motion associated with GIA. However, a coherent pattern of horizontal motion was not evident in the resulting velocity field. We adopted a recently published model of the British-Irish ice sheet to predict vertical crustal motion for a large number of spherically symmetric Earth viscosity models. Our results show that the adopted ice model is capable of producing a high-quality fit to the observations. The CGPS-derived estimates of vertical motion provide a useful constraint on the average value of viscosity within the upper mantle. Values of model lithospheric thickness and lower mantle viscosity are less well resolved, however. A suite of predictions based on an alternative ice model indicates that the vertical motion data are relatively insensitive to uncertainties in the ice loading history and so the constraints on upper mantle viscosity are robust.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".