Decoding surface processes from escarpment to watershed: Insights from karst landscapes using cosmogenic nuclides and geochemical data
Bibliographic record
Abstract
Tropical karst landscapes are marked by complex sediment dynamics resulting from the interplay between geomorphic processes and sediment transport . In the Vermelho Watershed (Brazilian savanna), we use paired cosmogenic nuclides ( 10 Be and 26 Al) to quantify denudation rates, burial durations, and sediment mixing. The spatial distribution of Al Be ratios reveals rapid erosion and prolonged burial on escarpments , in contrast to the more stable conditions of flatter areas, where erosion is subdued, and sediment residence time is longer. Comparisons with Iraquara and Serra das Mesas emphasize the influence of topography and sediment sources on nuclide inventories. Downstream increases in freshly eroded material point to fluvial mixing, while discrepancies between cosmogenic burial and OSL ages (Tarimba Cave) suggest partial burial and pre-depositional histories. The integration of cosmogenic, geochemical, and geomorphic data underscores the complexity of tropical karst systems, where vertical mixing and uneven erosion are key processes. These results contribute to a broader understanding of landscape evolution and offer a comparative basis for interpreting cosmogenic signals in fluvio-karst environments worldwide.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".