Contribution of ice dynamics along Nares Strait to the stability of ice arches
Bibliographic record
Abstract
Abstract Nares Strait, situated between northwest Greenland and Ellesmere Island, is an important conduit for exporting sea ice from the Arctic, especially thick multi-year ice undergoing an accelerated loss compared to other ice types. This export is impacted by ice arches that can form along the Strait and remain stable for months at a time resulting in a reduction in ice export. Arch stability is a function of sea ice thickness and there is a concern that the thinning of Arctic sea ice may weaken the arches resulting in an accelerated export of sea ice. However, little is known about the spatial and temporal variability of sea ice thickness along the Strait. Here we show that before arch formation, there is a local maximum in ice thickness where arches typically form, which is related to ice convergence. Furthermore, we demonstrate that ice motion continues north of the arch after it forms, resulting in convergence and a dynamic thickening of the sea ice. We propose that, even though thinning ice is a cause for concern, the dynamics of sea ice transport along Nares Strait lead to localized thickening of sea ice that may contribute to continued arch formation and stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".