Greenland glacial history, borehole constraints, and Eemian extent
Bibliographic record
Abstract
We examine the extent to which observations from the Greenland ice sheet combined with three‐dimensional dynamical ice sheet models and semi‐Lagrangian tracer methods can be used to constrain inferences of the Eemian evolution of the ice sheet, of the extent and frequency of summit migration during the 100 kyr ice age cycle, and of the deep geothermal flux of heat from the Earth into the base of the ice sheet. Relative sea level, present‐day surface geometry, basal temperature, and age and temperature profiles from the Greenland Ice Project (GRIP) are imposed as constraints to tune ice sheet model and climate forcing parameters. Despite the paucity of observations, model‐based inferences suggest a significant northeast gradient in geothermal heat flux. Our analyses also suggest that during the glacial cycle, the contemporaneous summit only occupied the present‐day location during interglacial periods. On the basis of the development and use of a high‐resolution semi‐Lagrangian tracer analysis methodology for δ18O, we rule out isotropic flow disturbances due to summit migration as a possible source of the high Eemian variability of the GRIP δ18O record. Finally, in contrast with results obtained in some recent attempts to infer the extent to which Greenland may have contributed to the anomalous highstand of Eemian sea level, we find that conservative bounds for this contribution are 2–5.2 m, with a more likely range of 2.7–4.5 m.
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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) | 0.000 | 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) | 0.002 | 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".