Laurentide ice sheet aspect ratio in models based on Glen’s flow law
Bibliographic record
Abstract
Abstract The problem of recovering the small aspect ratio of the ICE-4G reconstruction of the Last Glacial Maximum Laurentide ice sheet has proven to be a challenge for state-of-the-art thermomechanically-coupled three-dimensional ice-sheet models coupled to reduced climate models. Flow enhancements to Glen’s flow law, 20 to 30 times those required to adequately simulate the present-day Greenland ice sheet, have been found necessary in order to reproduce both the thickness and areal extent of the geophysical reconstruction. Within the confines of the Glen flow rheology, it is unclear what mechanism might explain the magnitude of this discrepancy in required flow enhancement for the Laurentide relative to the Greenland ice sheet We present a comparative analysis of three alternative explanations of such a questionable flow-law enhancement: radical changes to mass balance; radical changes to ice-sheet history; and strongly enhanced basal flows Based on this analysis, we argue that none of these alternatives provide a fully acceptable explanation for the small ICE-4G LGM aspect ratio of the Laurentide ice sheet, that has been inferred geophysically.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".