An improved glacial isostatic adjustment model for the British Isles
Bibliographic record
Abstract
Abstract The glacial isostatic adjustment (GIA) of the British Isles is of interest due to the constraints that can be provided on key model parameters such as the global meltwater signal, local ice sheet history and viscoelastic earth structure. A number of recent studies have modelled relative sea‐level (RSL) data from this region to constrain model parameters. As indicated in these studies, the sensitivity of these data to both local and global parameters results in a highly non‐unique problem. This study aims to address this inherent non‐uniqueness by combining a previously published British–Irish ice model that is based on the most recent geomorphological data with a new global ice sheet model that provides an accurate prediction of eustatic sea‐level change. In addition, constraints from Global Positioning System (GPS) measurements of present‐day vertical land motion are considered alongside the entirety of RSL data from both Great Britain and Ireland. A model solution is found that provides a high‐quality fit to both the RSL data and the GPS data. Within the range of earth viscosity values considered, the optimal data model fits were achieved with a relatively thin lithosphere (71 km), upper mantle viscosities in the range 4–6 × 10 20 Pa s and lower mantle viscosities ≥ 3 × 10 22 Pa s. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".