A review of radiometric analysis on soil erosion and deposition studies in Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Soil erosion is one of the main soil degradation phenomena that threaten sustainable use of soil productivity thus affecting food security. In addition, it leads to reservoir storage capacity loss because of sedimentation. This not only affects water quantity but also water quality. Worldwide, annual loss in reservoir storage capacity due to sedimentation is 0.5 to 1%. Similarly, about 27% of land in Africa is largely degraded by erosion. As a result, there is need to minimize soil erosion and deposition through site specific estimation of soil erosion and deposition rates in the reservoirs. To achieve this, Fallout RadioNuclides (FRNs) are some of the methods in use. The most common radionuclides include; <sup>137</sup>Cs, <sup>210</sup>Pb and <sup>7</sup>Be. Only few countries in Africa have exploited these FRNs. In these countries, <sup>137</sup>Cs has been largely exploited but in some regions, it has been reported to be below minimum detection limit. Using <sup>137</sup>Cs and <sup>210</sup>Pb, maximum reference inventory in Africa is found to be 1450 and 2602 Bq/m<sup>2</sup>, respectively. However, there is minimal application of <sup>7</sup>Be within the continent. Also, very little has been done in Africa to assess chronology and sedimentation rates of reservoirs using FRNs measured from sediment cores. In conclusion, a gap still exists on FRNs application in Africa in assessing soil erosion, deposition and reservoir sedimentation.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.013 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it