Impact of tension infiltrometer disc size on measured soil water repellency index
Bibliographic record
Abstract
Hunter, A. E., Chau, H. W. and Si, B. C. 2011. Impact of tension infiltrometer disc size on measured soil water repellency index. Can. J. Soil Sci. 91: 77-81. Accurate measurement of soil water repellency (or hydrophobicity) is important for assessing the hydraulic properties of soils. Water repellency index (RI), a measure of soil water repellency, can be determined using the tension infiltrometer. Little is known about the effects of different infiltrometer disc sizes on measured RI. Furthermore, the impact of method selection in the context of site assessment is unknown. The objective of this study was to determine if the infiltrometer disc size affects the measured RI. Studies were conducted on seven sandy and one clay site in Western Canada in 2008 and 2009. Mini (disc 4.5 cm in diameter) and standard (disc 20 cm in diameter) tension infiltrometers were used to determine RI. There was strong spatial variability in RI values at all sites. Higher RI and greater variance were associated with the smaller disc size due to the smaller zone of influence. Water repellency index values obtained from the mini and standard tension infiltrometers were not statistically different in most cases. We conclude that the mini infiltrometer is an appropriate method for site assessment of RI. The mini infiltrometer RI values were compared with those from the standard infiltrometer, resulting in a 44% accuracy rate with a type I error in 33% of the cases and a type II error in 22% of the cases.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".