Terminus change of Kaskawulsh Glacier, Yukon, under a warming climate: retreat, thinning, slowdown and modified proglacial lake geometry
Bibliographic record
Abstract
Abstract Links between proglacial lakes and glacier dynamics are poorly understood but are necessary to predict how mountain glaciers will react to a warmer, wetter climate, where such lakes are expected to increase both in number and volume. Here, we examine a long-term (~120 year) record of terminus retreat, thinning and surface velocities from in-situ and remote sensing observations at the terminus of Kaskawulsh Glacier, Yukon, Canada, and determine the impact of a local proglacial hydrological reorganisation on glacier dynamics. After an initial deceleration during the late 1990s, terminus velocities increased at a rate of 3 m a−2from 2000–12, while proglacial Slims Lake area increased simultaneously. The rapid drainage of the lake in May 2016 substantially altered the velocity profile, decreasing annual velocities by 48% within 3 km of the terminus between 2015 and 2021, at an average rate of ~ 12.5 m a−2. A key cause of the rapid drop in glacier motion was a reduction in flotation of the lower part of the glacier terminus after lake drainage. This has important implications for glacier dynamics and provides one of the first assessments of the impacts of a rapid proglacial lake drainage event on local terminus velocities.
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 | 0.000 | 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 | 0.001 | 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".