Infiltration of fine sediment into a coarse mobile bed: a phenomenological study
Bibliographic record
Abstract
Abstract Experiments were undertaken to study the nature of granular interaction in running water by examining the influence of fine grain inputs to a coarser sediment bed with a mobile surface. Video recordings of grain sorting by both kinetic sieving and spontaneous percolation are used to diagnose the critical processes controlling the overall bed response. Kinetic sieving takes place in the mobile bed surface, with the finer sediment moving to the bottom of the bedload transport layer at the interface with the underlying quasi‐static coarse bed. We show that the behavior at this interface dictates how a channel responds to a fine sediment input. If, by spontaneous percolation, the fine sediment is able to infiltrate into the underlying quasi‐static bed, the total transport increases and the channel degrades. However, if the fine sediment input rate exceeds the transport capacity or is geometrically unable to infiltrate into the underlying bed, it forms a quasi‐static layer underneath the transport layer that inhibits entrainment from the underlying bed, resulting in aggradation and an increase in bed slope. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".