Form and flow of the Devon Island Ice Cap, Canadian Arctic
Bibliographic record
Abstract
In this study, 3370 km of 100 MHz ice‐penetrating radar data were acquired from Devon Ice Cap, Arctic Canada. Bed returns were obtained from >90% of flight tracks. Mean crossing point errors in ice surface elevation and ice thickness were 7–8 m. Digital elevation models of ice cap surface and bed elevation, and ice thickness, were produced and can be used as boundary conditions in numerical modeling. Devon Ice Cap, including 1960 km2 of contiguous stagnant ice to its west, is 14,010 km2. The ice cap proper is 12,050 km2. Its largest drainage basin is 2630 km2. The ice cap crest has a maximum measured elevation of 1921 m. Maximum recorded ice thickness is 880 m. Ice cap volume is 3980 km3 (about 10 mm sea level equivalent). The bed, 8% of which lies below sea level, is an upland plateau dissected by steep‐sided valleys that control the locations of the major outlet glaciers which dominate ice cap drainage. About 73 km, 4%, of the ice cap margin ends in tidewater. The margin is not floating. Icebergs of <100 m were observed offshore. Only a single outlet glacier showed signs of past surge activity. All major outlet glaciers along the eastern ice cap margin have retreated 1–3 km since 1960. Synthetic aperture radar‐interferometic velocity structure shows slow, undifferentiated flow predominating in the west and center, with fast‐flowing outlet glaciers and intervening slow‐flowing ridges typical elsewhere. Outlet glacier velocities are 7–10 times higher than in areas of undifferentiated flow. This velocity structure, of fast‐flowing units within slower‐flowing ice, appears typical of many large (103 km2) Arctic ice caps.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".