In situ <sup>10</sup> Be modeling and terrain analysis constrain subglacial quarrying and abrasion at Jakobshavn Isbræ, Greenland
Bibliographic record
Abstract
Abstract. Glacial erosion creates diagnostic landscapes and vast amounts of sediment. Yet, knowledge about the rate by which glaciers erode and sculpt bedrock and the proportion of quarried (plucked) versus abraded material is limited. To address this, we quantify subglacial erosion rates and constrain the ratio of quarrying to abrasion during the 19th/20th century overriding of a bedrock surface fronting Jakobshavn Isbræ, Greenland, by combining 10Be analyses, a digital terrain model, and field observations. Cosmogenic 10Be measurements along a 1.2-m-tall quarried bedrock step reveal a triangular wedge of quarried rock. Using individual 10Be measurements from abraded surfaces across the study area, we derive an average abrasion rate of 0.13±0.08 mm yr-1. By applying this analysis across a ~1.33 km2 study area, we estimate that the Greenland Ice Sheet quarried 378±45 m3 and abraded 322±204 m3 of material at this site. These values result in an average total erosion rate of 0.26±0.16 mm yr-1 with abrasion and quarrying contributing in roughly equal proportions within uncertainty. Additional cosmogenic 10Be analysis and surface texture mapping indicate that many lee steps are relict from the prior glaciation and were not re-quarried during the recent overriding event. These new observations of glacier erosion in a recently exposed landscape provide one of the first direct measurements of quarrying rates and indicate that quarrying accounts for roughly half of total glacial erosion in representative continental shield lithologies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".