Holocene pore‐ice δ<sup>18</sup>O and δ<sup>2</sup>H records from drained thermokarst lake basins in the Old Crow Flats, Yukon, Canada
Bibliographic record
Abstract
Abstract Thermokarst lakes form following the thaw of ice‐rich permafrost and drain after a few decades to millennia. Drained thermokarst lake basins (DTLBs) become epicenters for peat accumulation and re‐aggradation of ice‐rich permafrost. This re‐aggradation of permafrost may be interrupted by subsequent thermokarst lake formation with sufficient disturbance. Thermokarst lakes and DTLBs are abundant near Old Crow, Yukon, Canada, but little is known about their evolution through the Holocene. In this study, we investigate the hydrology and drainage histories of seven DTLBs from the Old Crow Flats on the basis of cryostratigraphy, radiocarbon dating, and pore‐ice δ18O and δ2H records. Cryostratigraphic evidence implies only one of the seven studied DTLBs underwent multiple thermokarst cycles. Radiocarbon age–depth models demonstrate a slowdown in the rate of post‐drainage peat accumulation with time. Pore‐ice isotope analyses reveal a spectrum of possible post‐drainage isotopic histories resulting from spatial variability in permafrost, vegetation, and hydrology. Unlike lacustrine silt, post‐drainage peat contains relatively constant pore‐ice isotope trends. In light of our findings, we propose that syngenetic peat permafrost in DTLBs preserve a warm‐season sampling of local meteoric waters. These pore‐ice δ18O and δ2H records may aid millennial‐scale paleoclimate investigations, as we demonstrate through our reconstruction of Holocene climate change in northern Yukon.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".