Retreat of Northern Hemisphere Marine‐Terminating Glaciers, 2000–2020
Bibliographic record
Abstract
Abstract We mapped the terminus position for every marine‐terminating glacier in the Northern Hemisphere for 2000, 2010, and 2020, including the Greenland Ice Sheet, to provide the first complete measure of their variability. In total, these 1,704 glaciers lost an average of 389.7 ± 1.6 km 2 a −1 (total 7,527 ± 31 km 2 ) from 2000 to 2020 with 123 glaciers becoming no longer marine‐terminating over this period. Overall, 85.3% of glaciers retreated, 2.5% advanced, and the remaining 12.3% did not change outside of uncertainty limits. Outlet glaciers of the Greenland Ice Sheet are responsible for 61.9% of total area loss, although their rate of retreat was 34% less in 2010–2020 than 2000–2010. Glaciers with the largest area loss terminate in ice shelves or ice tongues, are surge‐type, have an unstable basal geometry, or have an unusually wide calving margin.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".