Near‐shore talik development beneath shallow water in expanding thermokarst lakes, Old Crow Flats, Yukon
Bibliographic record
Abstract
Abstract It is generally assumed that permafrost is preserved beneath shallow lakes and ponds in the Western North American Arctic where water depth is less than about two thirds of the late‐winter lake ice thickness. Here we present field observations of talik development beneath water as shallow as 0.2 m despite a lake ice thickness of 1.5 m, in Old Crow Flats (OCF), YT. Conditions leading to the initiation and development of taliks beneath shallow water were investigated with field measurements of shore erosion rates, bathymetry, ice thickness, snow accumulation, and lake bottom temperature near the shores of two expanding lakes in OCF. The sensitivity of talik development to variations in lake bottom thermal regime was then investigated numerically. Where ice reached the lake bottom, talik development was controlled by the ratio of freezing degree days to thawing degree days at the lake bottom (FDDlb/TDDlb). In some cases, spatial variations in on‐ice snow depth had a minimal effect on annual mean lake bottom temperature (Tlb) but caused sufficient variations in FDDlb/TDDlb to influence talik development. Where Tlb was close to but greater than 0°C simulations indicated that the thermal offset allowed permafrost aggradation to occur under certain conditions, resulting in irregular near‐shore talik geometries. The results highlight the sensitivity of permafrost to small changes in lake bottom thermal conditions where the water column freezes through in early winter and indicate the occurrence of permafrost degradation beneath very shallow water in the near‐shore zone of Arctic ponds and lakes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".