On the characteristics of sea ice divergence/convergence in the Southern Beaufort Sea
Bibliographic record
Abstract
Abstract. An understanding of spatial gradients in sea ice motion, or deformation, is essential to understanding of ocean-sea-ice-atmosphere interactions and realistic representations of sea ice in models used for the purposes of prediction. This is particularly true for the southern Beaufort Sea, where significant offshore hydrocarbon resource development increases the risk of oil and other contaminants dispersing into the marginal ice zone. In this study, sea ice deformation is examined through evaluation of ice beacon triplets from September to November 2009 in the southern Beaufort Sea (SBS), defined according to distance from the coastline on deployment. Results from this analysis illustrate that ice beacon triplets in the SBS demonstrate spatiotemporal differences in their evolution at the periphery and interior of the ice pack. The time rate of change in triplet area highlights two intervals of enhanced divergence and convergence in fall, 2009. Investigation of sea ice and atmospheric conditions during these intervals shows that until mid-September, all triplets respond to northerly flow, while during the second interval of enhanced divergence/convergence in October only one triplet responds to persistent northeasterly flow due to its proximity to the ice edge, in contrast to triplets located at the interior of the pack. Differences in sea ice deformation and dispersion near the pack ice edge and interior are further demonstrated in the behavior of triplets B and C in late October/early November. The results from this analysis highlight differences in dispersion and deformation characteristics based on triplet proximity to the southernmost ice edge and coastline, with implications for modeling studies pertaining to sea ice dynamics and dispersion.
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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 | 0.001 |
| 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) | 0.001 | 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".