Cobble-bed concentrations and vegetated banks: effects on flow
Bibliographic record
Abstract
The effect of cobble concentration and vegetated banks on the mean flow and turbulence of streams has not yet been investigated. Cobble concentrations ranging from 10 to 30 cobbles/m 2 were tested by this study. In total, 27 velocity profiles were measured using an acoustic Doppler velocimeter (ADV) at a sampling frequency of 200 Hz. The results show that cobble concentration affects the mean velocity and turbulence intensity profiles close to the vegetated bank, especially near the bed, but does not influence the RS distribution. This experimental study reveals a Z-shaped Reynolds stress (RS) distribution near the vegetated bank without any negative values, but a convex distribution at the centre of flume with negative values near the water surface. Negative RS values are associated with dominant effects of the inward and outward events near the water surface. The effect of cobble concentration on the frequency of bursting events is not considerable, based on the quadrant analysis.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".