Stream barb performance in a semi-alluvial meandering channel
Bibliographic record
Abstract
A series of seven stream barbs were installed at two consecutive channel bends in Sawmill Creek, a semi-alluvial stream located in Ottawa, Canada.Stream barbs (also known as submerged groynes) are low-profile linear rock structures that extend from the outside bank regions of channel bends in an upstream direction, to redirect the attacking currents and prevent erosion of the bank.As well as providing bank protection, these structures promote vegetated stream banks, create resting pools and scour holes for fish habitat, and increase biodiversity for aquatic species.Despite these benefits, because of their relative novelty as river training structures, stream barbs are not a common means of stream bank protection in Canada and are possibly non-existent for semi-alluvial or clay channels.Three years of monitoring and measurement of flow conditions (discharge, water velocity and depth) and bathymetry, before (2 years) and after (1 year) the construction of the barbs, have been collected at the Sawmill Creek study site, providing valuable data for understanding their performance in a semi-alluvial channel.Sawmill Creek has a predominately clay bed and banks, presenting a rare opportunity to study the unique dynamics between flow and sediment transport within a clay channel.This paper reports on (i) the unique site conditions and monitoring methodology; (ii) preliminary results of the 3 year monitoring program; and (iii) recommendations for future design and implementation of these structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".