Intra-annual and intra-seasonal flow dynamics of a High Arctic polythermal valley glacier
Bibliographic record
Abstract
Abstract Measurements of surface dynamics on polythermal John Evans Glacier, Nunavut, Canada, over two winter periods and every 7–10 days throughout two melt seasons (June–July 2000, 2001) provide new insight into spatio-temporal patterns of High Arctic glacier dynamics. In the lower ablation zone, mean annual surface velocities are 10–21 m a–1, but peak velocities up to 50% higher are attained during late June/early July. In the upper ablation zone and lower accumulation zone, mean annual surface velocities are typically 10–18 m a–1, and peak velocities up to 40% higher occur during late July. In the upper accumulation zone, mean annual surface velocities are 2–9 m a–1, and motion in mid- to late July exceeds this by up to 10%. Rapid drainage of ponded supraglacial water in the upper ablation zone to an initially distributed subglacial drainage system in mid-June may force excess surface motion in the warm-based lower glacier. The data indicate that the duration of the velocity response may be related to the rate of channelization of the basal drainage, and the velocity response may be transmitted up-glacier by longitudinal coupling. An increase in surface velocities in the middle glacier in late July occurs in conjunction with the opening of two further moulins in the accumulation zone.
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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".