A new technique for rapid measurement of continuous soil moisture characteristic curves
Bibliographic record
Abstract
The soil moisture characteristic (SMC) curve of a soil describes the relationship between the soil suction (tension in the soil pore water) and its water content. The majority of traditional methods used to obtain SMC curves involve gathering individual point measurements of soil water content over a range of applied soil suctions, and then fitting a curve through these points. Each point measurement requires at least a day of testing to gather, leading to a total testing time of weeks to assemble the whole SMC curve. This paper presents a technique to obtain a complete, continuous SMC curve in a total preparation and testing time of 3–5 days. During evaporative drying of the soil specimen under examination, a digital laboratory balance and a high-capacity tensiometer, both connected to a data acquisition system, monitor continuous pore water loss and suction data respectively. The tensiometer is composed of a pressure transducer for suction measurement and an extremely fine porous ceramic that interfaces between the specimen and the transducer. To date, the technique has been successfully applied to resedimented, non-clay soils. Experimental results from the new method are in agreement with results from capillary fall tests. The paper also provides some insight into tensiometer behaviour and features of SMC curves.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".