Experiments on the grain size gap in river bed sediments
Bibliographic record
Abstract
Riverbed sediments often lack fine gravel between 1 and 5 mm, a phenomenon referred to as the ‘grain size gap’. The gap corresponds to the rapid reduction in grain size associated with the gravel-sand transition, where median bed material grain size reduces from ~10 mm gravel to ~1 mm sand. Fine gravel grain sizes are often present in hillslope sediment, so it is not clear why they are absent on riverbed surfaces. We present a phenomenological laboratory experiment examining changes in sediment dynamics across a gravel-sand transition to explore the fate of grain size gap material. Our observations indicate that where sand falls out of washload, forming persistent surficial deposits at the gravel-sand transition, grain size gap material experiences enhanced mobility. This is due to hydraulic smoothing by sand that occurs because of a geometric effect, where medium sand bridges interstitial pockets in fine gravel bed surfaces. Our experiments show that fine gravel flux is enhanced by sand deposition making gravel beds at the threshold of motion, mobile. We are unable to maintain an immobile fine gravel bed when sand is fed, which explains why gravel beds composed of 1 to 5 mm particles are so rare on Earth. Our experiment shows that fine gravel particles mobilized by sand deposition are transported out of the flume. We hypothesize that in natural systems, fine gravel particles are either buried in the diffuse extension of gravel-sand transitions or transported into coastal and marine environments where they are more commonly observed.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".