A new procedure for the determination of soil-water retention curves by continuous drying using high-suction tensiometers
Bibliographic record
Abstract
Soil-water retention curves (SWRCs) can be determined using high-suction tensiometers (HSTs) following two different procedures that involve either continuous or discrete measurement of suction. In the former case, suction measurements are taken while the sample is permanently exposed to the atmosphere and the soil is continuously drying. In the latter case, the drying or wetting process is halted at different stages to ensure equalization within the sample before measuring suction. Continuous drying has the advantage of being faster; however, it has the disadvantage that the accuracy of mass measurements (necessary for the determination of water content) is affected by the weight and stiffness of the cable connecting the HST to the logger. To overcome this problem, an alternative continuous drying procedure is presented in this paper in which two separate but nominally identical samples are used to obtain a single SWRC; one sample is used for the mass measurements, while a second sample is used for suction measurements. It is demonstrated that the new continuous drying procedure gives SWRCs that are similar to those obtained by discrete drying.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".