Influence of the sediment supply texture on morphological adjustments in gravel‐bed rivers
Bibliographic record
Abstract
Abstract The role played by the texture of the sediment supply on channel bed adjustments in gravel‐bed rivers is poorly understood. To address this issue, an experimental campaign has been designed. Flume experiments lasting 96 h in a 9 m long, 0.60 m wide have been performed with different sand‐gravel mixtures as feed textures. The response of the surface texture has been found to be highly dependent on the grain size distribution of the feed. When the feed texture included gravel, the finest fractions of the sediment supply infiltrate beneath the surface. Conversely, sand remains on the surface when the feed texture lacks gravel. This different textural response becomes obscured when water discharge increases. Further, the sediment transport rate approaches the feed rate differently depending on the content of gravel in the feed texture. When a small proportion of gravel is part of the feed texture, bed load transport rate asymptotically approaches the feed rate. However, when a significant fraction of gravel is part of the feed grain size distribution, bed load transport rate approaches the feed rate by following an oscillatory path. These findings have been verified in terms of a one‐dimensional numerical model. This modeling reveals that the higher the differences in mobility among the grain sizes contained in the feed texture, the more evident is the nonasymptotic transient trend toward equilibrium.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".