Paleolimnology of thermokarst lakes: a window into permafrost landscape evolution
Bibliographic record
Abstract
Widespread across northern permafrost landscapes, thermokarst ponds and lakes provide vital wildlife habitat and play a key role in biogeochemical processes. Stored in the sediments of these typically shallow and dynamic waterbodies are rich sources of paleoenvironmental information whose potential has not yet been fully exploited, likely because of concerns over stratigraphic preservation and challenges to develop reliable sediment core chronologies. Here, we present an overview of recently derived informative paleolimnological reconstructions based on multiparameter analysis of sediment archives from permafrost aquatic basins. We include examples from across the Canadian North, Alaska, and Siberia that illustrate their value for providing insights into temporal patterns of lake inception, catchment erosion, aquatic productivity, hydrological evolution, and landscape disturbances. Although not captured in our survey, emerging research directions focused on carbon accumulation, storage, and balance hold much promise for contributing to global climate change science.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".