Sorting of a sand–gravel mixture in a Gilbert‐type delta
Bibliographic record
Abstract
Abstract This paper presents the results of a Gilbert‐type delta progradation experiment within an impoundment created by a dam. The delta was composed of a poorly sorted sand–gravel mixture in a bedload‐dominated environment. The main goal of the paper is to analyse the sorting process of material within the deposit as the delta progrades towards the dam. Bed profile evolution has been documented and the entire delta has been extensively sampled in order to study sorting processes. Longitudinal and vertical sorting mechanisms are illustrated. What is novel in this investigation is the complete record, within an entire deltaic deposit, of the vertical distribution of streamwise sorting in the absence of suspended load. The data presented herein provide a detailed description of sorting processes in a Gilbert‐type delta. The experimental set‐up, the water flow and the sediment feed rate chosen determine the evolution of the delta: it initially progrades with little topset aggradation and degrades afterwards. Experimental results fit well with a previously presented empirical sorting model, despite the fact that the experimental conditions used here were well outside the range of those used to derive that model. The relative coarsening of the upper layers of the delta is found to be related to the slow speed at which the delta progrades, the formation of a mobile armour layer and the erosion of the topset towards the end of the run. Furthermore, a strong correlation between the coarsening of the bottom layer of the delta and its front height has been documented and explained: as the delta gets higher, as there is more space to sort sediment, it is more likely that coarse particles failing near the top of the foreset reach the bottom of the foreset. These findings provide new and useful data documenting sediment sorting in granular, bedload‐dominated deltas.
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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) | 0.001 | 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".