Effect of flow depth and velocity on the scales of macroturbulent structures in gravel‐bed rivers
Bibliographic record
Abstract
Laboratory and field data show that the length of macroturbulent structures consistently scales with flow depth (Y). Scalings with average streamwise flow velocity (U) only exist for laboratory data. Our aim is to establish the relations between macroturbulent structures, low‐speed wedges and ejections, and U and Y in gravel‐bed rivers. Fifteen velocity profiles covering a wide range of U while controlling for Y were measured. The duration (time interval between the beginning and the end of an event) and length (distance between two successive similar events) of the macroturbulent events are analyzed. Strong scalings of the duration and length of the low‐speed wedges and ejections exist for Y. Ejection length is strongly related to U. Because the sampling design ensured the statistical independence between U and Y, these results should provide robust estimates of the scalings of macroturbulent structures in gravel‐bed rivers.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".