Possibility of Stabilizing the Greenland Ice Sheet
Bibliographic record
Abstract
Abstract Recent acceleration in the retreat of the Greenland ice sheet under a warming climate has caused unprecedented challenges and threats to coastal communities due to the rising sea level and increasing storm surges. This raises a critical question from a climate mitigation perspective: Would there still be a chance to stabilize the Greenland ice sheet if the carbon reduction goals of the Paris Agreement could be met? Here, we show that there is indeed a possibility for stabilizing the Greenland ice sheet with the low‐emission scenario of RCP2.6. In particular, RCP2.6 would potentially limit the warming in Greenland below 1°C within next 30 years and constrain its loss of ice sheet coverage below 10%. After 2050, the annual mean temperature in Greenland is likely to be stabilized and no further loss is expected to its ice sheet. However, the effective window for this chance will be closing after 2020. If no effective carbon reduction policies are being taken now, we are very likely to enter a continuous warming pathway and lose the chance of stabilizing the Greenland 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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".