Bibliographic record
Abstract
Abstract. The largest regional drivers of current surface elevation increases in the Antarctic Ice Sheet are associated with ice flow reconfiguration in previously active ice streams, highlighting the important role of ice dynamics in responding to climate change. Here, we investigate controls on the evolution of the flow configuration of the Vanderford and Totten Glaciers – key outlet glaciers of the Aurora Subglacial Basin, the most rapidly thinning region of the East Antarctic Ice Sheet. We review factors that influence the ice flow in this region, and use an ice sheet model to investigate the sensitivity of the catchment divide location to thinning at Vanderford Glacier associated with ongoing retreat, and thickening at Totten Glacier associated with an intensification of the east-west snowfall gradient. The present-day catchment divide between the Totten and Vanderford Glaciers is not constrained by the geology or topography, but is determined by the large-scale ice sheet geometry and its long-term evolution in response to climate forcing. Furthermore, the catchment divide is subject to migration under relatively small changes in surface elevation, leading to ice flow and basal water piracy from Totten to Vanderford Glacier. Our findings show that ice flow reconfigurations do not only occur in regions of West Antarctica like the Siple Coast, but also in the east, motivating further investigations of past, and potential for future, ice flow reconfigurations around the whole Antarctic coastline. Such modelling of ice flow and basal water piracy may require coupled ice sheet thermomechanical and subglacial hydrology models, constrained by field observations of subglacial conditions. Our results also have implications for ice sheet mass budget studies that integrate over catchments, and the validity of the zero flow assumption when selecting sites for ice core records of past climate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.016 | 0.008 |
| Insufficient payload (model declined to judge) | 0.530 | 0.378 |
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".