Seasonal and spatial variability in dissolved organic matter quantity and composition from the Yukon River basin, Alaska
Bibliographic record
Abstract
The seasonal and spatial variability of dissolved organic matter (DOM) quantity and chemical composition were investigated in the Yukon River basin of Alaska, United States, and northwestern Canada. Dissolved organic carbon (DOC), chromophoric DOM (CDOM), and dissolved lignin phenols were measured across a range of source waters and the seasonal hydrograph. Strong relationships were determined between CDOM and both DOC and lignin phenols, highlighting the potential for deriving detailed spatial and temporal distributions of DOM composition from CDOM monitoring. Maximum concentrations of measured parameters were observed during the spring flush, when DOM had a remarkably high content of aromatic vascular plant material derived from surface soil and litter layers. A larger portion of riverine DOM was attributed to vascular plant sources than previously believed by utilizing representative vegetation leachates and a soil pore water as end‐members. In combination with recent studies highlighting export of young, labile DOM during the spring flush in northern high‐latitude river systems, our results suggest riverine DOM is less degraded and more labile than previously thought with clear ramifications for its biomineralization or photo‐oxidation in marine environments.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".