EFFECT OF GRAVEL PARTICLE SIZE ON THE RESHAPING OF DYNAMIC REVETMENTS
Bibliographic record
Abstract
Gravel beaches are prevalent natural features on many coastlines and play a vital role in shore protection, often inspiring protection structures (Bayle et al., 2020) and nature-based solutions. Dynamic revetments are constructed features, designed to mimic gravel beaches, dissipating wave energy and preventing or limiting erosion. Compared to sand beaches, gravel revetments dissipate incident wave energy and dampen backwash intensity by percolating through the relatively large pore volume space (Komar, 2007). During storm events, gravel particles move up the beach, accreting at the crest. This predominately onshore-directed transport of gravel material differs from the storm-driven morphodynamic behaviour of sandy beaches, which tend to exhibit higher rates of offshore-directed transport (Komar, 2007). Ahrens’ Theorem continues to be used as a design volume estimator for dynamic revetments (Bayle et al., 2020). This primary objective of this study is to investigate how dynamic revetments with different D50 reshape under various wave conditions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".