High Arctic channel incision modulated by climate change and the emergence of polygonal ground
Bibliographic record
Abstract
Stream networks in Arctic and high-elevation regions underlain by frozen ground (i.e., permafrost) are expanding and developing in response to accelerating global warming, and intensifying summertime climate variability. The underlying processes governing landscape dissection in these environments are varied, complex and challenging to unravel due to air-temperature-regulated feedbacks and shifts to new erosional regimes as climate change progresses. Here we use multiple sources of environmental information and physical models to reconstruct and understand a 60-year history of landscape-scale channelization and evolution of the Muskox Valley, Axel Heiberg Island. A time series of air photographs indicates that freeze-thaw-related polygon fields can form rapidly, over decadal time scales. Supporting numerical simulations show that the presence of polygons can control how surface runoff is routed through the landscape, exerting a basic control on channelization, which is sensitive to the timing, duration and magnitude of hydrograph events, as well as seasonal air temperature trends. These results collectively highlight that the occurrence and dynamics of polygon fields modulate channel network establishment in permafrost-rich settings undergoing changes related to a warming climate.
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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 | 0.000 |
| 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) | 0.001 | 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".