Recent changes in thickness of the Devon Island ice cap, Canada
Bibliographic record
Abstract
Long‐term rates of thickness change were derived at several spatial scales using a variety of methods for most of the Devon Island ice cap, Nunavut, Canada. Basin‐wide thickness change calculations were derived for the accumulation zones of all major drainage basins as the area‐averaged volume difference between balance and InSar fluxes at the altitude of the long‐term equilibrium line (ELA). Thickness changes for ablation zones were derived as a function of the surface mass balance, flux across the EL and calving flux, averaged across the ablation areas. Average rates of thickness change are near zero in the accumulation zones of the northern and southwestern basins but reach −0.23 ± 0.11 m a−1 w.e. in the southeast basin due to dynamic thinning. Thickness changes were also estimated along five major outlet glaciers as a function of flux divergence and net surface mass balance and along the Belcher Glacier by comparing elevation values derived from 1960s aerial photography with those derived from 2005 NASA Airborne Topographic Mapper (ATM) surveys. Ice dynamics have had a significant influence on the pattern of thickness change of all outlet glaciers examined in this study. Volume changes derived from the basin‐wide values indicate a net loss of −76.8 ± 7 km3 water equivalent from the main portion of the ice cap from 1960 to 1999, contributing 0.21 ± 0.02 mm to global sea level over this time. This value is ∼44% greater than previous estimates of volume change based on volume‐area scaling methods and surface mass balance alone.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".