Large-scale integrated subglacial drainage around the former Keewatin Ice Divide, Canada reveals interaction between distributed and channelised systems
Bibliographic record
Abstract
Despite being widely studied, subglacial meltwater landforms are typically mapped and investigated individually, thus the drainage system as a whole remains poorly understood. Here, we identify and map all visible traces of subglacial meltwater flow across the Keewatin sector of the former Laurentide Ice Sheet from the ArcticDEM, generating significant new insights into the connectedness of the drainage system. Due to similarities in spacing, morphometry and spatial location, we suggest that the 100s-1000s m wide features often flanking and connecting sections of eskers (i.e. tunnel valleys, meltwater tracks and esker splays) are varying expressions of the same phenomena and collectively term these features ‘meltwater corridors’. Based on observations from contemporary ice masses, we propose a new formation model based on the pressure fluctuations surrounding a central conduit, in which the esker records the imprint of the central conduit and the wider meltwater corridors the interactions with the surrounding distributed drainage system, or variable pressure axis (VPA). We suggest that the widespread aerial coverage of meltwater corridors across the Keewatin sector provides constraints on the extent of basal uncoupling induced by basal water pressure fluctuation and variations in spatial distribution and evolution of the subglacial drainage system, which have important implications for ice sheet dynamics.
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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 | 0.001 | 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) | 0.002 | 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".