Geophysical constraints on the dynamics and retreat of the Barents Sea ice sheet as a paleobenchmark for models of marine ice sheet deglaciation
Bibliographic record
Abstract
Abstract Our understanding of processes relating to the retreat of marine‐based ice sheets, such as the West Antarctic Ice Sheet and tidewater‐terminating glaciers in Greenland today, is still limited. In particular, the role of ice stream instabilities and oceanographic dynamics in driving their collapse are poorly constrained beyond observational timescales. Over numerous glaciations during the Quaternary, a marine‐based ice sheet has waxed and waned over the Barents Sea continental shelf, characterized by a number of ice streams that extended to the shelf edge and subsequently collapsed during periods of climate and ocean warming. Increasing availability of offshore and onshore geophysical data over the last decade has significantly enhanced our knowledge of the pattern and timing of retreat of this Barents Sea ice sheet (BSIS), particularly so from its Late Weichselian maximum extent. We present a review of existing geophysical constraints that detail the dynamic evolution of the BSIS through the last glacial cycle, providing numerical modelers and geophysical workers with a benchmark data set with which to tune ice sheet reconstructions and explore ice sheet sensitivities and drivers of dynamic behavior. Although constraining data are generally spatially sporadic across the Barents and Kara Seas, behaviors such as ice sheet thinning, major ice divide migration, asynchronous and rapid flow switching, and ice stream collapses are all evident. Further investigation into the drivers and mechanisms of such dynamics within this unique paleo‐analogue is seen as a key priority for advancing our understanding of marine‐based ice sheet deglaciations, both in the deep past and in the short‐term future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".