Joint Stochastic Bedload Transport and Bed Elevation Model: Variance Regulation and Power Law Rests
Bibliographic record
Abstract
We describe the joint dynamics of bedload transport and bed elevation changes with a stochastic population model, and we analyze (1) the dependence of bedload flux statistics on local bed elevations and (2) resting time distributions for sediment undergoing burial in the fluctuating sedimentary bed. The model involves entrainment and deposition in a control volume characterized by elevation‐dependent rates, and it exhibits a statistical regulation effect, whereby bed aggradation suppresses the variance of the bedload flux while degradation enhances it. This variance regulation effect is contingent on collective entrainment, whereby moving grains destabilize stationary grains in a positive feedback. When collective entrainment is turned off,bedload transport fluctuations become independent of the bed elevation. Return times from above in the bed elevation time series provide heavy‐tailed power law distributions of resting times with tail behavior characterized by the mean erosion rate and the active layer depth. These results imply bedload statistics measurements on relatively short timescales can be strongly biased by bed elevation changes when collective entrainment occurs, and they support the growing consensus that sediment burial generates heavy‐tailed sediment resting times that ultimately generate anomalous bedload diffusion.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".