Temporal Development of Scour Holes around Submerged Stream Deflectors
Bibliographic record
Abstract
Deflector structures used in many fish habitat rehabilitation schemes are frequently overtopped, yet few studies have examined the scour patterns created around submerged models. Furthermore, laboratory studies typically test smooth-surfaced structures, whereas those installed in natural rivers are generally made of logs or boulders. This study uses rough-surfaced paired deflectors to investigate the temporal evolution of scour for three overtopping ratios in identical approach flow conditions in a flume. Results show that maintaining identical discharge and raising the deflector height, which reduces the overtopping ratio (i.e., flow depth divided by structure height), generates increased depth and volume of scour next to the structures. The location of maximum depth and the rate of scouring with time is similar for the two highest deflectors (overtopping ratios of 1.22 and 1.83), but different for the lowest deflector model (overtopping ratio of 3.67). To improve the success rate of river restoration projects using in-stream structures, the overtopping ratio should be considered in equations that predict the scour depth evolution with time.
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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 | 0.001 |
| 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) | 0.001 | 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".