Mass balance of Devon Ice Cap, Canadian Arctic
Bibliographic record
Abstract
Abstract Interferometric synthetic aperture radar data show that Devon Ice Cap (DIC), northern Canada, is drained through a network of 11 glacier systems. More than half of all ice discharge is through broad flows that converge to the southeast of the ice cap, and these are grounded well below sea level at their termini. A calculation of the ice-cap mass budget reveals that the northwestern sector of DIC is gaining mass and that all other sectors are losing mass. We estimate that a 12 489 km 2 section of the main ice cap receives 3.46±0.65 Gt of snowfall each year, and loses 3.11±0.21 Gt of water through runoff, and 1.43±0.03 Gt of ice through glacier discharge. Altogether, the net mass balance of DIC is –1.08±0.67 Gt a –1 . This loss corresponds to a 0.003 mma –1 contribution to global sea levels, and is about half the magnitude of earlier estimates.
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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".