Ice sheet action versus reaction: Distinguishing between Heinrich events and Dansgaard‐Oeschger cycles in the North Atlantic
Bibliographic record
Abstract
Glaciers and ice sheets play an active role in the climate system and the global hydrological cycle. The stability of continental ice sheets must be better understood for assessments of future sea level rise and to uncover the causes of millennial‐scale climate variability that characterized the last glacial period. Ice‐rafted debris (IRD) in the midlatitude oceans and subpolar seas tells of widespread calving of icebergs from the Northern Hemisphere ice sheets during the last glacial period, but the climatic implications of this IRD are unclear. Does the sediment record indicate repeated dynamical collapse of the ice sheets, with ice sheets actively forcing the climate system? Alternatively, were ice sheet margins simply advancing and retreating in response to climate vacillations? On the basis of simulations of iceberg delivery to the ocean during the last glacial cycle we argue that the marine record exemplifies both of these phenomena. Heinrich events were clearly episodes of internal dynamical instability of the Laurentide Ice Sheet, while millennial‐scale IRD is more simply interpreted as a response of the circum‐Atlantic ice sheets to Dansgaard‐Oeschger climate cycles. Ice sheets in different coastal regions respond differently to climate fluctuations, but overall iceberg fluxes increase in cold periods, peaking within a few centuries of climatic cooling. Regions with relatively warm, wet climates (Scandinavia, western North America, and Svalbard) are the most sensitive to millennial climate variability, with rapid response times and large millennial variability in iceberg fluxes.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".