Mass balance of ice caps in the Queen Elizabeth Islands, Arctic Canada: 2014-2015
Bibliographic record
Abstract
In-situ glacier mass balance surveys were conducted by Natural Resources Canada in April/May 2016 across the Devon, Meighen, South Melville, and Agassiz Ice Caps, Queen Elizabeth Islands. Survey results indicate significantly negative values over all ice caps in the 2014-2015 mass balance year with Meighen and Melville Ice Caps experiencing the fourth most negative mass balance year on record thinning by -115 and -89 cm respectively while the Devon Ice Cap, which thinned by -39 cm, experienced the sixth most negative year on record. After the relatively cool summers of 2013 and 2014, extremely negative mass balance values for 2014-2015 are more consistent with the post-2005 trend during which melt rates of high Arctic glaciers have been 3-5 times more negative than the long-term (1960-2013) average. The climatic net mass balance measurements from the Agassiz and Devon (NW) Ice Caps indicated an increase of the Equilibrium Line Altitude by 300 m and 400 m respectively relative to the long-term means. Associated water equivalent mass loss of 0.68, 0.052, and 0.053 Gt for the Devon (NW), Meighen, and South Melville Ice Caps respectively indicate a net positive contribution to global sea-level rise from these three sites for the 2014-2015 balance year.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".