Effects of heterogeneous land use/cover types on river channel morphology in the Solo River catchment, Eastern Uganda
Bibliographic record
Abstract
In the tropics, unmonitored land use/cover types cause significant effects on the narrowing and widening of river channels which affects the integrity of water resources. River channel planform extent was characterized using Landsat images, while water and bedload samples were collected and analysed for a period of one year. The results revealed that in 1986, the channel planform covered 3.7 sq km in length than in 2013 where it increased to 4.2 sq km. Wetland (537.1mgl−1) and bushland (186.3mgl−1) cover types had the highest concentration of suspended sediments. Fine sand (0.25 mm), silty sand (1 mm) and silty clay (0.125 mm) bedload particle types dominated the riverbed along the channel from the sampled land use/cover types. The high concentration of sediments, bedload materials, bank instability, and streamflow were significant contributors to the narrowing and widening of the channel (p < 0.05). Agricultural land use was the major contributor of channel aggradation (0.8 m) and degradation (0.25 m) compared to tree plantations, bushlands, forest and wetland cover types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".