Bibliographic record
Abstract
ABSTRACT The term thermokarst describes the processes and landforms that involve collapse of the land surface as a result of the melting of ground ice. We review the literature that has contributed to our understanding of patterns, processes and feedbacks, and the environmental consequences of thermokarst, focusing on hillslope, thaw lake and wetland processes. Advances in remote sensing techniques, and their application in a broad suite of change detection studies, indicate recent increases in the rates and magnitude of thermokarst including retrogressive thaw slumping, lake expansion and the transformation of frozen peatlands to collapsed wetlands. Field‐based studies and modelling have enhanced the knowledge of processes and feedbacks associated with warming permafrost, changes in talik geometry and accelerated thaw slump activity, and thaw lake expansion. Hydrological processes can strongly influence the rates of thaw lake and gully development, and the degradation of frozen peatlands. Field studies and calibrated modelling efforts that investigate the drivers of thermokarst and test conceptual ideas of landscape evolution will be critical to further advance the prediction of landscape and ecosystem change. Thermokarst research provides an important context for studying the environmental implications of permafrost degradation. Hillslope thermokarst can alter the water quality of lakes and streams with implications for aquatic ecosystems. Investigation of the interactions between thermokarst and hydrologic and ecological processes has improved knowledge of the feedbacks that accelerate change or lead to stabilisation in terrestrial and thaw lake environments. Finally, the influence of permafrost thaw on soil carbon dynamics will be an important focus of thermokarst research because of feedbacks with the global climate system. Copyright © Her Majesty the Queen in Right of Canada 2013.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".