Evaluation of the Infiltration Capacity of Soils in Akpabuyo Local Government Area of Cross River, Nigeria
Bibliographic record
Abstract
The study evaluates the infiltration capacity of soils in Akpabuyo Local Government Area of Cross River State. The double ring infiltrometer with inner ring of 30cm and outer ring of 50cm diameter with a height of 30cm above the ground was used by the researcher to measure infiltration rates on bare and crusted lands, sparsely vegetated and forested surfaces. Three runs were done at each location. Soil samples were collected from ten sampling points using a soil auger at a depth ranging from 0-15cm. Samples on soil types were collected because it was believed that soil type greatly influences the rate of infiltration in soil. The results revealed that the mean of sand, silt and clay was 70.3, 15.4 and 14.3 per cent respectively. This shows that the soil in the study area was dominated by sandy soil. The “crust factor” calculated for the area of study was 0.0530. Also the research revealed that the mean of infiltration rate for forested surface with value of 158.8mm/hr was higher than that of sparsely vegetal and bare surfaces which have values of 66.5 and 8.43mm/hr respectively. Wanton destruction of vegetal cover promotes surface sealing by direct raindrop impact on soil surface and it has inhibited rapid percolation of water on the bare surface of the study area. It is recommended that to improve physical properties and infiltration rate of soils in the study area afforestation should be encourage to cushion the effect of deforestation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".