Mapping thermal and hydrological conditions beneath a polythermal glacier with radio-echo sounding
Bibliographic record
Abstract
Abstract Spatial patterns in residual bed reflection power (BRPr), derived from ground-based radio-echo sounding, were mapped and interpreted in terms of the thermal and hydrological conditions at the base of a high-Arctic polythermal glacier (John Evans Glacier, Ellesmere Island, Canada). BRPr is the residual from a statistical relationship between measured bed reflection power and ice thickness that describes the rate of dielectric loss with depth in the glacier. We identified three types of thermal structure: (a) Positive BRPr and an internal reflecting horizon occur over the glacier terminus. The reflecting horizon is interpreted as the boundary between warm and cold ice, and suggests the presence of a warm basal layer. (b) Positive BRPr occurs without an internal reflector in the upper part of the ablation zone. This suggests that ice is at the pressure-melting point only at the bed. (c) Negative BRPr without an internal reflector occurs in all other regions, suggesting cold ice at the bed. Where BRPr is positive, its pattern is similar to the pattern of subglacial water flow predicted from the form of the subglacial hydraulic equipotential surface. This suggests that hydrological conditions at the glacier bed are a major control on BRPr, probably because the dielectric contrast between ice and water is higher than that between ice and other subglacial materials.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".