Predicting vegetation‐stabilized dune field morphology
Bibliographic record
Abstract
The morphology of vegetation‐stabilized dune fields on the North American Great Plains (NAGP) mostly comprises parabolic dunes; stabilized barchan and transverse dunes are rare, with the exception of transverse and barchan mega‐dunes in the Nebraska Sand Hills. We present a hypothesis from a numerical dune field model explaining the vegetation‐stabilized morphology of dunes under unidirectional wind. Simulations with a range of initial dune morphologies (closely‐spaced transverse to disperse barchans) indicate that stabilized morphology is determined by the ratio of slipface deposition rate to deposition tolerance of vegetation. Slipface deposition rate is related to dune height, flux, and celerity. With a fixed depositional tolerance, large, slow‐moving dunes have low slipface deposition rates and ‘freeze’ in place once vegetation is introduced. Relatively small, fast dunes have high slipface deposition rates and evolve into parabolic dunes, often colliding during stabilization. Our hypothesis could explain differences in stabilized morphology across the NAGP and elsewhere.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".