The effect of coarse gravel on cohesive sediment entrapment in an annular flume
Bibliographic record
Abstract
Abstract. While cohesive sediment generally represents a small fraction (<0.5%) of the total sediment mass stored in gravel-bed rivers, it can strongly influence physical and biogeochemical processes in the hyporheic zone and alter aquatic habitat. This research was conducted to examine mechanisms governing the interaction of cohesive sediments with gravel beds in the Elbow River, Alberta, Canada. A series of erosion and deposition experiments with and without a gravel bed were conducted in a 5-m diameter annular flume. The critical shear stress for deposition and erosion of cohesive sediment without gravel was 0.115 Pa and 0.212 Pa, respectively. In experiments with a gravel bed, cohesive sediment moved from the water column into the gravel bed via the coupling of surface and pore water flow. Once in the gravel bed, cohesive sediments were not mobilized under the maximum applied shear stresses (1.11 Pa) used in the experiment. The gravel bed had an entrapment coefficient (ratio between the entrapment flux and the settling flux) of 0.2. Accordingly, when flow conditions are sufficient to produce a shear stress that will mobilize the armour layer of the gravel bed (>16 Pa), cohesive materials trapped within the gravel bed will be entrained and transported into the Glenmore Reservoir, where sediment-associated nutrients may pose treatment challenges to the drinking water supply.
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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 | 0.001 | 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".