Experiments on the grain size gap across gravel-sand transitions
Bibliographic record
Abstract
An abrupt transition in river bed grain size occurs from gravel to sand over a short downstream distance, often only a few channel widths, and is termed the gravel-sand transition (GST). At this point, the bed structure also changes from framework- to matrix-supported. Whether the GST is externally imposed, a result of internal dynamics (sediment sorting, abrasion, suspension deposition) or due to some other emergent property is unclear. There is also a general absence of rivers beds with median surface grain sizes between ~1 and 5 mm, often referred to as the grain size gap. Here we present two sets of new laboratory experiments, examining changes in fluid and sediment dynamics across the GST. In the first set, we created stable GSTs with a 10 mm gravel and 0.5 mm sand that show GST formation is consistent with previous theory suggesting that at shear velocities of ~0.1 m/s, sand particles rapidly fall out of suspension as a result of a particle Reynolds number dependency (i.e. a viscous effect). In a second set of experiments, we explored the fate of grain size gap material. We formed a gravel wedge composed of ~2 to 5 mm sediment, then fed 0.5 mm sand. Our observations indicate that where sand rapidly starts to fall out of suspension, the gravel bed becomes inherently unstable. Gravel is transported downstream until the grain size gap material is largely exhausted from the system (e.g. buried under sand or rafted out of the flume). This occurs because sand sized particles fill or bridge interstitial pockets in the fine gravel bed surface, generating fluid acceleration in the near-bed region (i.e. a geometric effect specific to these grain sizes). As such, particles in the grain size gap do not form the dominant mode in river bed sediments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".