Ice sheet scale subglacial meltwater conduit dimensions and processes: insights from 3D morphometry of a large sample of eskers
Bibliographic record
Abstract
Meltwater exerts an important influence on ice sheet dynamics and has attracted an increasing amount of attention over the last 20 years. However, the active subglacial environment remains difficult to study mainly due to its inaccessibility. Understanding of the dimensions, pattern, and extent of subglacial meltwater conduits at the ice sheet scale is limited to relatively sparse observations. We address this gap by using the geomorphological record of Quaternary ice sheets as a proxy to quantify the dimensions and pattern of subglacial conduits at the ice sheet scale. We present the results of a high-resolution (2 m), large sample (n>50,000) study of three-dimensional esker morphometry at sample locations in SW Finland and Nunavut, Canada. Detailed mapping of esker crestlines and outlines permits the quantification of a number of parameters, including: length, width, height, cross-sectional area, volume, sinuosity, cross-sectional symmetry, and uphill/downhill trends. Whilst the dimensions of eskers reflect depositional processes as well as simply the size of the parent conduit, they nevertheless offer a powerful tool for understanding the size and shape of meltwater conduits and the configuration of subglacial drainage systems across large areas (entire ice sheets), and over long periods of time (from years to thousands of years) in both high spatial and temporal resolution. The results may be used to: (1) inform numerical models of subglacial meltwater drainage, (2) inform process models of esker formation, and (3) provide a dataset of esker morphometry against which other features may be compared (e.g. sinuous ridges on Mars).
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".