Bibliographic record
Abstract
Abstract Ice-stream shear margins are the lateral boundaries of narrow, fast-flowing bands of ice within an ice sheet. We develop a theory for the migration of shear margins over time driven by viscous dissipation of heat within the ice, focusing on widening of the ice stream. The location of the margin is modelled as a transition from a cold to a temperate ice-sheet bed, and simultaneously as the transition from no slip to free slip at the same location. The temperature field in the ice is affected by intense shear heating as well as by the migration velocity of the margin (i.e. by the widening rate of the ice stream); if migration is too fast, there is little time for the ice to warm up and the margin remains cold, causing the bed to freeze. This suppresses widening. Conversely, if the migration speed is too slow, the ice in the margin warms up, causing the bed on the far side of the cold–temperate transition to reach the melting point, and migration to speed up. Using a Wiener–Hopf method, we show that for a given far-field shear stress, geothermal heat flux, and ice geometry, there is a single migration velocity that balances the two effects and permits widening at a steady rate. This velocity increases with the far-field lateral shear stress imposed by the ice stream, which controls shear heating in the margin. Our results also indicate that (i) a region of temperate ice must form in the margin, and that (ii) lateral advection of ice may play a significant role in controlling migration speeds.
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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 | 0.000 | 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) | 0.002 | 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".