Dimensionless argument: a narrow grain size range near 2 mm plays a special role in river sediment transport and morphodynamics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. The grain size 2 mm is the conventional border between sand and gravel. This size is used extensively, and generally without much physical justification, to discriminate between such features as sedimentary deposit type (clast-supported versus matrix-supported), river type (gravel bed versus sand bed), and sediment transport relation (gravel versus sand). Here we inquire as to whether this 2 mm boundary is simply a social construct upon which the research community has decided to agree or whether there is some underlying physics. We use dimensionless arguments to show the following for typical conditions on Earth, i.e., natural clasts (e.g., granitic or limestone) in 20 ∘C water. As grain size ranges from 1 to 5 mm (a narrow band including 2 mm), sediment suspension becomes vanishingly small at normal flood conditions in alluvial rivers. We refer to this range as pea gravel. We further show that bedload movement of a clast in the pea gravel range with, for example, a size of 4 mm moving over a bed of 0.4 mm particles has an enhanced relative mobility compared to a clast with a size of 40 mm moving over a bed of the same 4 mm particles. With this in mind, we use 2 mm here as shorthand for the narrow pea gravel range of 1–5 mm over which transport behavior is distinct from both coarser and finer material. The use of viscosity allows the delineation of a generalized dimensionless bed grain size discriminator between “sand-like” and “gravel-like” rivers. The discriminator is applicable to sediment transport on Titan (ice clasts in flowing methane/ethane liquid at reduced gravity) and Mars (mafic clasts in flowing water at reduced gravity), as well as Earth.
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.
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 | 0.000 | 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 | 0.000 |
| 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 it