Efficacy of bedrock erosion by subglacial water flow
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Bedrock erosion by sediment-bearing subglacial water remains little-studied; however, the process is thought to contribute to bedrock erosion rates in glaciated landscapes and is implicated in the excavation of tunnel valleys and the incision of inner gorges. We adapt physics-based models of fluvial abrasion to the subglacial environment, assembling the first model designed to quantify bedrock erosion caused by transient subglacial water flow. The subglacial drainage model consists of a one-dimensional network of cavities dynamically coupled to one or several Röthlisberger channels (R-channels). The bedrock erosion model is based on the tools and cover effect, whereby particles entrained by the flow impact exposed bedrock. We explore the dependency of glacial meltwater erosion on the structure and magnitude of water input to the system, the ice geometry, and the sediment supply. We find that erosion is not a function of water discharge alone, but also depends on channel size, water pressure, and sediment supply, as in fluvial systems. Modelled glacial meltwater erosion rates are 1 to 2 orders of magnitude lower than the expected rates of total glacial erosion required to produce the sediment supply rates we impose, suggesting that glacial meltwater erosion is negligible at the basin scale. Nevertheless, due to the extreme localization of glacial meltwater erosion (at the base of R-channels), this process can carve bedrock (Nye) channels. In fact, our simulations suggest that the incision of bedrock channels several centimetres deep and a few metres wide can occur in a single year. Modelled incision rates indicate that subglacial water flow can gradually carve a tunnel valley and enhance the relief or even initiate the carving of an inner gorge.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it