Tidewater glacier fluctuations in central East Greenland coastal and fjord regions (1980s–2005)
Bibliographic record
Abstract
Abstract Summer 2000/01 ASTER and Landsat 7 scenes and semi-automated digitization were used to compile a glacier inventory for local glaciers of the Geikie Plateau region, central East Greenland. Of the 332 glaciers (41 591 km2), 120 are tidewater-terminating and drain 90% of the glacierized area. Differencing the 2000/01 tidewater margins from the 1980s GEUS map database ice polygons (113 glaciers) and from 2004/05 ASTER tidewater margins (78 glaciers) shows a cumulative tidewater terminus width decrease from 196 km to 183 km between the 1980s and 2000s, with a corresponding areal loss of ~31 km2 and an effective length change of –14.3 km. Between 2000/01 and 2004/05, areal loss was 26 km2. Average margin retreat rate increased two- to threefold, from 1.7–2.1km2 a–1 (1980s– 2000) to 3.9–5.7km2 a–1 (2000–05). Advances are negligible, apart from two surges, of which one was previously undetected. Coastal, ‘outer’ fjord-terminating, glaciers have two to three times larger areal and effective length retreat rates than ‘inner’ fjord-terminating glaciers. We investigate possible causes and hypothesize that, in addition to ocean temperature and sea ice, changes in sea fog may affect coastal-terminating more than inner fjord-terminating glaciers.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".