Exploring Canyons Beneath Devon Ice Cap for Sub-Glacial Drainage Using Radar and Thermodynamic Modeling
Bibliographic record
Abstract
Sub-glacial canyon features up to 580m deep between broad, flat mesas were identified beneath Devon Ice Cap, Devon Island, Nunavut, Canada during a recent Radar Echo Sounding (RES) survey. The largest canyon connects a hypothesized area of distributed sub-glacial water near the ice cap's summit with the marine-terminating Sverdrup outlet glacier. This canyon represents a probable drainage route for the hypothesized sub-glacial water system. Radar bed reflectivity is consistently 30 dB lower along the canyon floor than on the mesas, contradicting the signature expected in the presence of sub-glacial water. We compare these data with radar backscattering simulations to demonstrate that the reflectivity pattern may be topographically induced. Our simulated results indicated a 10m wide canal-like water feature is unlikely along the canyon floor averaging ~300m wide, however, smaller features may be difficult to detect via RES. We calculated basal temperature profiles along the canyon using a 2-D finite difference method, and found basal conditions at the canyon floor may be significantly warmer than at the mesas. Despite elevated temperatures, there is limited evidence that the basal environment along the canyon floor could support a connected drainage system between the Devon Ice Cap summit and Sverdrup Glacier. The complex terrain beneath Devon Ice Cap demonstrates some limitations for RES. Future studies should carefully consider attenuation correction methods near steep or complex terrain, and seek validation of RES analyses with multiple methods, as we have demonstrated here.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".