Bibliographic record
Abstract
Abstract. During the glacial cycles of the past 800 thousand years, Eurasia and North America were periodically covered by large ice sheets. While the Late Pleistocene glacial cycles typically lasted 80 – 120 thousand years, the termination phases only took 10 thousand years to complete. During these glacial terminations, the North American and Eurasian ice sheets retreated which created large proglacial lakes in front of the ice sheet margin. Proglacial lakes accelerate the deglaciation as they can facilitate ice shelves in the southern margins of the North American and the Eurasian ice sheets. Ice shelves are characterized by basal melting, low surface elevations and negligible friction at the base. Here we quantify the effect of proglacial lakes, and the combined effect with glacial isostatic adjustment (GIA) on Late Pleistocene glacial terminations. We find that proglacial lakes accelerate the deglaciation of the ice sheets mainly because of the absence of basal friction underneath ice shelves. If the friction underneath grounded ice is applied to floating ice, we find that full deglaciation is postponed by a few millennia, the Barents-Kara Sea region does not fully deglaciate, and there are no extensive ice shelves. Additionally, the large uncertainty in melt rates underneath lacustrine ice shelves translates to an uncertainty in the timing of the termination of only a few centuries at most. Proglacial lakes are created by the depression in the landscape that linger after the ice sheet has retreated. The depth, size and timing of proglacial lakes depend on the bedrock rebound. We find that if the bedrock rebounds within a few centuries, instead of a few millennia, the mass loss rate of the ice sheet is substantially reduced. This is because fast bedrock rebound prevents the formation of extensive proglacial lakes. Additionally, a decrease in thickness is partly compensated by the faster bedrock rebound, resulting in a higher surface elevation with lower temperatures and higher surface mass balance delaying deglaciation. We find that a very long bedrock relaxation time does not affect terminations substantially, but will lead to a later inception of the next glacial period. This is because initial inception regions, such as North-Western Canada, remain below sea level throughout the preceding interglacial period.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.025 | 0.021 |
| Insufficient payload (model declined to judge) | 0.203 | 0.156 |
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".