Determining the permeability of soil at Universiti Malaysia Pahang, Gambang Campus using guelph permeameter kit
Bibliographic record
Abstract
The measure of the soil's ability to permit water to flow through its pores or voids is termed as permeability. Different types of soil give different value of permeability because their abilities to permit water to flow through their pores are different. Several factors that affect the permeability of the soil are type of soil, vegetation management, surface moisture, soil compaction, rainfall intensity and temperature. This study was carried out to determine the permeability of the soil and identify the soil classification for ten locations in the compound of Universiti Malaysia Pahang, Gambang Campus. Guelph Permeameter test was used to determine the permeability of soil of each location. The lowest permeability of soil is at Guard house and construction site 2 with the rate of 0 cm/sec while the highest is at sport complex with the rate of 2.19x10 4 cm/sec. The results indicated the slow permeability at the ten locations were due to less voids in the soil structures.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".