Changes in Sediment Transport of the Yellow River in the Loess Plateau
Bibliographic record
Abstract
Sediment erosion is a pressing problem throughout the world as it leads to loss of resources such as agricultural land. Soil erosion most commonly occurs as a result of the forces exerted by wind and water. Human induced landscape change can expedite soil erosion due to removal of vegetation, urbanization and rangeland grazing (to name a few). Sediment erosion can lead to increased sediment input to nearby rivers which can alter river channel morphology through increased sediment deposition. Sediment transport in rivers is also important on a global scale as sediments carry organic carbon from the land to oceans via river channels (Ludwig et al., 1996). River sediment levels depend largely on the surrounding landscape. Areas where the soil is being impacted directly through activities such as cultivation and urbanization will generally contribute large amounts of sediment to a nearby channel. As seen over the last century, high river sedimentation can lead to issues with drinking water quality and engineering structures such as reservoirs. In order to manage the landscape effectively, soil conservationists in the United States developed a universal soil loss equation during the 1950’s (Wischmeier, 1976). The soil loss of an area is calculated as follows,
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".