Reconciling geodetic and geologic estimates of coastal vertical land motion around the British Isles
Bibliographic record
Abstract
Karegar et al. (2016, GRL) showed that independent estimates of vertical land motion from geodetic and geologic techniques are critical for understanding coastal surface motion caused by geological versus human-induced processes along the Atlantic coast of North America. Motivated by these results, we extend our analysis to the British Isles where good quality and spatially dense constraints are available from a continuous GNSS network and a state-of-the-art Holocene sea-level database. Glacial Isostatic Adjustment (GIA) along the Atlantic coast of North America causes the land surface to sink (up to -1.5 mm/yr), exacerbating tidal-induced flooding effects of sea-level rise. The British Isles are also subjected to proglacial forebulge collapse associated with the GIA response to the ancient Fennoscandian and British-Irish Ice Sheets. Here, we present an up-to-date and precise analysis based on continuous GNSS (combined GPS and GlONASS observations) and geologic records of late Holocene sea-level change to examine residuals between rates on these different timescales to determine if there is a significant residual and, if so, the processes responsible for the rate change.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".