Forty-seven Years of Research on the Devon Island Ice Cap, Arctic Canada
Bibliographic record
Abstract
ABStRACt. The Devon Island ice cap has been the subject of scientific study for almost half a century, beginning with the first mass balance measurements in 1961. Research on the ice cap was the first to investigate (1) the role of meltwater in seasonal ice-velocity variations on a polythermal Arctic ice cap, (2) the use of air temperature rather than net radiation as a proxy for the energy driving surface melt, and (3) the influence of the changing frequency of specific synoptic weather config-urations on glacier melt and mass balance. Other research has included investigations of ice cap geometry, flow dynamics, and mass balance; ice core analyses for records of past climate and contaminant deposition; and studies of changes in ice cap area and volume and their relationship to surface mass balance and ice dynamics. Current research includes ground studies connected to efforts to calibrate and validate the radar altimeter that will be carried by the European Space Agency’s (ESA) CryoSat2 satellite, and a major collaborative Canadian International Polar Year (IPY) project focused on the Belcher Glacier, on the northeast side of the ice cap, that examines hydrodynamics of large tidewater glaciers. This paper summarizes our current knowledge of the Devon Island ice cap and identifies some of the outstanding questions that continue to limit our understanding of climate-ice cap interactions in Arctic regions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".