Influences of glacier melt and permafrost thaw on the age of dissolved organic carbon in the Yukon River basin
Bibliographic record
Abstract
Abstract Responses of near‐surface permafrost and glacial ice to climate change are of particular significance for understanding long‐term effects on global carbon cycling and carbon export by high‐latitude northern rivers. Here we report Δ 14 C‐dissolved organic carbon (DOC) values and dissolved organic matter optical data for the Yukon River, 15 tributaries of the Yukon River, glacial meltwater, and groundwater and soil water end‐member sources draining to the Yukon River, with the goal of assessing mobilization of aged DOC within the watershed. Ancient DOC was associated with glacial meltwater and groundwater sources. In contrast, DOC from watersheds dominated by peat soils and underlain by permafrost was typically enriched in Δ 14 C indicating that degradation of ancient carbon stores is currently not occurring at large enough scales to quantitatively influence bulk DOC exports from those landscapes. On an annual basis, DOC exported was predominantly modern during the spring period throughout the Yukon River basin and became older through summer‐fall and winter periods, suggesting that contributions of older DOC from soils, glacial meltwaters, and groundwater are significant during these months. Our data indicate that rapidly receding glaciers and increasing groundwater inputs will likely result in greater contributions of older DOC in the Yukon River and its tributaries in coming decades.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".