Relation between rock uplift and denudation from cosmogenic nuclides in river sediment in the Central Alps of Switzerland
Bibliographic record
Abstract
A north‐south traverse through the Swiss Central Alps reveals that denudation rates correlate with recent rock uplift rates in both magnitude and spatial distribution. This result emerges from a study of in situ–produced cosmogenic 10 Be in riverborne quartz in Central Alpine catchments. As a prerequisite, we took care to investigate the potential influence of shielding from cosmic rays due to snow, glaciers, and topographic obstructions; to calculate a possible memory from Last Glacial Maximum (LGM) glaciation; and to identify a watershed size that is appropriate for systematic sampling. Mean denudation rates are 0.27 ± 0.14 mm/a for the Alpine foreland and 0.9 ± 0.3 mm/a for the crystalline Central Alps. The measured cosmogenic nuclide‐derived denudation rates are in good agreement with post‐LGM lake infill rates and are about twice as high as denudation rates from apatite fission track ages that record denudation from 9 to 5 Ma. In general, denudation rates are high in areas of high topography and high crustal thickness. The similarity in the spatial distribution and magnitude of denudation rates and those of rock uplift rates can be interpreted in several ways: (1) Postglacial rebound or climate change has introduced a transient change in which both uplift and denudation follow each other with a short lag time; (2) the amplitude of glacial to interglacial changes in both is small and is contained in the scatter of the data; (3) both are driven by ongoing convergence where their similarity might hint at some form of long‐term quasi steady state; or (4) enhanced continuous Quaternary erosion and isostatic compensation of the mass removed accounts for the distribution of present‐day rock uplift.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".