A new inventory of mountain glaciers and ice caps for the Antarctic periphery
Bibliographic record
Abstract
Abstract Although the glaciers in the Antarctic periphery make up a large fraction of all mountain glaciers and ice caps on Earth, a detailed glacier inventory of the region is lacking. We compile such an inventory, recording areas, area-altitude distributions, terminus characteristics and volume estimates. Glaciers on the mainland are excluded. The inventory is derived from the Antarctic Digital Database and some manual digitization. We additionally rely on satellite imagery, digital elevation models and a flowshed algorithm to classify ice bodies. We find 1133 ice caps and 1619 mountain glaciers covering a total of 132 867 ± 6643 km 2 . Estimated total volume corresponds to 0.121 ± 0.010 m sea-level equivalent. Of the total glacier area, 99% drains either into ice shelves (63%) or into the ocean (36%). The inventory will provide a database for glacier mass-balance assessments, modelling and projections, and help to reduce the uncertainties in previous studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 teacher head, 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".