Morphodynamics of small‐scale superimposed sand waves over migrating dune bed forms
Bibliographic record
Abstract
The kinematics and morphodynamics of low‐amplitude, small‐scale sand waves developed over migrating dunes are examined using data drawn from laboratory experiments. We refer to the superimposed features as “sand sheets,” a general descriptive term for low‐amplitude bed waves that are not easily classified as ripples, dunes, or bars. Within the experiments, the sheets formed downstream of the reattachment point at a distance that was invariant with dune size. Some sheets lacked slip faces composed of sand grains avalanching down a slope near the angle of repose. Over equilibrium dunes, three to four sand sheets were observed per 100 s. Sheet thickness was 10% of the height of the dune upon which they were superimposed; they migrated at 8 to 10 times the dune rate; they had nearly constant lengths over the full range of dune lengths and flow conditions; and they had aspect ratios of ∼0.025. Dunes and sand sheets represent distinct scales of sediment transport with different migration rates. However, sediment transport rates, calculated from the sand sheet and dune morphologies, are nearly identical. For transport equivalence to occur, sand sheets migrating at 10 times the dune rate must be 0.1 times the size, which is consistent with the morphological observations. Superimposed bed waves on dunes are often considered simply as additional roughness elements, but these results indicate that such bed waves are the agency by which the dune bed form itself moves downstream.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".