Iceberg calving flux and mass balance of the Austfonna ice cap on Nordaustlandet, Svalbard
Bibliographic record
Abstract
Satellite radar interferometry, 60 MHz airborne ice‐penetrating radar data, and visible band satellite imagery were used to calculate the velocity structure, ice thickness, and the changing ice‐marginal extent of Austfonna (8000 km 2 and 2500 km 3 ), the largest ice cap in the Eurasian Arctic. Ice cap motion is generally less than about 10 m a −1 , except where faster flowing curvilinear features with velocities of several tens to over 200 m a −1 are present. Most drainage basins of Austfonna have undergone ice‐marginal retreat over the past few decades at an average of a few tens of meters per year. Integrating margin change around the whole ice cap gives a total area loss of about 10 km 2 a −1 . Iceberg flux from the marine margins of Austfonna is about 2.5 ± 0.5 km 3 a −1 (water equivalent), about 45% of the total calving flux from the whole Svalbard archipelago. When mass loss by iceberg production is taken into account, the total mass balance of Austfonna is negative by between about 2.5 and 4.5 km 3 a −1 . This iceberg flux represents about 33 ± 5% of total annual mass loss from Austfonna, with the remainder lost through surface ablation. Iceberg flux should be included in calculations of the total mass balance of the many large Arctic ice caps, including those located in the Russian and Canadian Arctic that end in tidewater. The neglect of this term has led to underestimates of mass loss from these ice caps and, thus, to underestimates of the contribution of Arctic ice caps to global sea level rise.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".