Seasonal Variation in Sediment Oxygen Demand in a Northern Chained River-Lake System
Bibliographic record
Abstract
Sediment oxygen demand (SOD) contributes immensely to hypolimnetic oxygen depletion. SOD rates thus play a key role in aquatic ecosystems’ health predictions. These rates, however, can be very expensive to sample. Moreover, determination of SOD rates by sediment diagenesis modeling may require very large datasets, or may not be easily adapted to complex aquatic systems. Water quality modeling for northern aquatic systems is emerging and little is known about the seasonal trends of SOD rates for complex aquatic systems. In this study, the seasonal trend of SOD rates for a northern chained river-lake system has been assessed through the calibration of a water quality model. Model calibration and validation showed good agreement with field measurements. Results of the study show that, in the riverine section, SOD20 rates decreased from 1.9 to 0.79 g/m2/day as urban effluent traveled along the river while a SOD20 rate of 2.2 g/m2/day was observed in the lakes. Seasonally, the SOD20 rates in summer were three times higher than those in winter for both river and lakes. The results of the study provide insights to the seasonal trend of SOD rates especially for northern rivers and lakes and can, thus, be useful for more complex water quality modeling studies in the region.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".