pySBeLT: A Python software package for stochasticsediment transport under rarefied conditions
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Bibliographic record
Abstract
Granular sediment of various sizes moves downstream along river beds when water flow is capable of entraining particles from the bed surface. This process is known as bed load sediment transport because the particles travel close to the boundary. It is common to treat the transport process as a predictive problem in which the mean transport rate past a stationary observation point is a function of local water flow conditions and the grain size distribution of the bed material However, a predictive approach to the bed load problem neglects the stochastic nature of transport due to the movements of individual particles (Einstein, 1937; Here, we present an open-source Python model, pySBeLT, which simulates the kinematics of rarefied particle transport (low rates) as a stochastic process along a riverbed profile. pySBeLT is short for Stochastic Bed Load Transport. The primary aim of pySBeLT is to offer an efficient and reasonable numerical means to probe connections between individual particle motions and local transport rates, or the flux. We suggest that pySBeLT is a suitable teaching tool to help introduce bed load transport to advanced undergraduate and graduate students alike.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it