Sediment resuspension mechanisms and their contributions to high‐turbidity events in a large lake
Why this work is in the frame
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Bibliographic record
Abstract
Abstract High‐resolution field data, collected during April to October of 2008–2009, were analyzed to investigate the quantitative contribution of sediment resuspension to high‐turbidity events in central Lake Erie. Resuspension events were distinguished within high‐turbidity events according to turbidity, fluorescence and acoustic backscatter timeseries, as well as satellite images. We observed 16 high‐turbidity events, causing a total duration of ∼20 d (out of 344 d) with elevated nearbed turbidity (> 10 NTU). Of these events, 64% were correlated with algal biomass, with the remaining 18%, 5%, and 4% being attributed to sediment resuspension by surface waves, storm‐generated currents and enhanced nearbed turbulence induced by high‐frequency internal waves, respectively. This is the first time that resuspension by enhanced nearbed turbulence from high‐frequency linear internal wave degeneration has been observed in a large lake. Resuspension was parameterized as a function of the instantaneous critical bottom velocity, bottom shear stress and the Shields parameter. From the in situ measurements, we suggest an extended Shields diagram for silty bed material that can be used to predict resuspension in other aquatic systems with similar sediment composition (∼20% cohesive sediment).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 it