A map of large Canadian eskers from Landsat satellite imagery
Why this work is in the frame
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Bibliographic record
Abstract
Meltwater drainage systems beneath ice sheets are a poorly understood, yet fundamentally important environment for understanding glacier dynamics, which are strongly influenced by the nature and quantity of meltwater entering the subglacial system. Contemporary sub-ice sheet meltwater drainage systems are notoriously difficult to study, but we can utilise exposed beds of palaeo-ice sheets to further our understanding of subglacial drainage. In particular, eskers record deposition in glacial drainage channels and are widespread on the exposed beds of former ice sheets. This paper presents a 1:5,000,000 scale map of >20,000 large eskers (typically > 2 km long) deposited by the Laurentide Ice Sheet (LIS), mapped from Landsat imagery of Canada, in order to establish a dataset suitable for analysis of esker morphometry and drainage patterns at the ice sheet scale. Comparisons between eskers mapped from Landsat imagery and aerial photographs indicate that, in most areas, approximately 75% of eskers are detected using Landsat. The data presented in this map build on and extend previous work in providing a consistent map of an unprecedented sample of eskers for quantitative analysis. It offers an alternative perspective on the problems surrounding ice-sheet meltwater drainage and can be used for: (i) detailed investigations of esker morphometry and distribution from a large sample size; (ii), testing of numerical models of meltwater drainage routing that predict esker characteristics (e.g. channel spacing, sinuosity), (iii) assessment of the factors that control esker location and formation; and (iv), a refined understanding of ice margin configurations during retreat of the LIS.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.007 | 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 it