From soil aggregates to riverine flocs: a laboratory experiment assessing the respective effects of soil type and flow shear stress on particles characteristics
Bibliographic record
Abstract
Abstract Particles eroded from hillslopes and exported to rivers are recognized to be composite particles of high internal complexity. Their architecture and composition are known to influence their transport behaviour within the water column relative to discrete particles. To‐date, hillslope erosion studies consider aggregates to be stable once they are detached from the soil matrix. However, lowland rivers and estuaries studies often suggest that particle structure and dynamics are controlled by flocculation within the water column. In order to improve the understanding of particle dynamics along the continuum from hillslopes to the lowland river environment, soil particle behaviour was tested under controlled laboratory conditions. Seven flume erosion and deposition experiments, designed to simulate a natural erosive event, and five shear cell experiments were performed using three contrasting materials: two of them were poorly developed and as such can not be considered as soils, whilst the third one was a calcareous brown soil. These experiments revealed that soil aggregates were prone to disaggregation within the water column and that flocculation may affect their size distribution during transport. Large differences in effective particle size were found between soil types during the rising limb of the bed shear stress sequence. Indeed, at the maximum applied bed shear stress, the aggregated particles median diameter was found to be three times larger for the well‐developed soil than for the two others. Differences were smaller in the falling limb, suggesting that soil aggregates underwent structural changes. However, characterization of particles strength parameters showed that these changes did not fully turn soil aggregates into flocs, but rather into hybrid soil aggregate–floc particles. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".