Examining the interaction between multi‐year landfast sea ice and the Mertz Glacier Tongue, East Antarctica: Another factor in ice sheet stability?
Bibliographic record
Abstract
The Mertz Glacier tongue (MGT), East Antarctica, has a large area of multi‐year fast sea ice (MYFI) attached to its eastern edge. We use various satellite data sets to study the extent, age, and thickness of the MYFI and how it interacts with the MGT. We estimate its age to be at least 25 years and its thickness to be 10–55 m; this is an order of magnitude thicker than the average regional sea‐ice thickness and too thick to be formed through sea‐ice growth alone. We speculate that the most plausible process for its growth after initial formation is marine (frazil) ice accretion. The satellite data provide two types of evidence for strong mechanical coupling between the two types of ice: The MYFI moves with the MGT, and persistent rifts that originate in the MGT continue to propagate for large distances into the MYFI. The area of MYFI decreased by 50% following the departure of two large tabular icebergs that acted as pinning points and protective barriers. Future MYFI extent will be affected by subsequent icebergs from the Ninnis Glacier and the imminent calving of the MGT. Fast ice is vulnerable to changing atmospheric and oceanic conditions, and its disappearance may have an influence on ice tongue/ice shelf stability. Understanding the influence of thick MYFI on floating ice tongues/ice shelves may be significant to understanding the processes that control their evolution and how these respond to climate change, and thus to predicting the future of the Antarctic Ice Sheet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".