Shrinking lakes of the Arctic: Spatial relationships and trajectory of change
Bibliographic record
Abstract
[1] Over the past 3 decades the Arctic has seen substantial warming. Previous local to regional scale studies have shown a considerable reduction in the size of lakes in this region. The subsequent exposure of carbon- and methane-rich sediments and the direct changes in surface albedo feed back into the drivers of regional and global climate change. Understanding and quantifying changes in the Arctic is a critical component of climate modeling due to the cooling effect of the Arctic on the global climate. The current work utilizes global satellite data from the Moderate Resolution Imaging Spectro-radiometer (MODIS) instrument to investigate changes in lakes across Canada between 2000 and 2009. The results show a net reduction of more than 6,700 km2 in the surface area of water in lakes across Canada. Modest gains in the southern regions are offset by larger losses in surface area farther north. Additionally, spatial analysis shows that the lakes showing change are clustered in groups. This suggests that local variability may play a role in the observed changes. Further work is needed to extend the analysis to the circumpolar Arctic.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".