Establishing soil-water characteristic curve and determining unsaturated hydraulic conductivity of kaolin by ultracentrifugation and electrical measurements
Bibliographic record
Abstract
To establish soil-water characteristic curves (SWCCs) of fine-grained soils, researchers have employed geotechnical centrifuges. However, most of these studies were confined to small acceleration levels and as a result the suction, psi, created in the soil mass was extremely low (< 100 kPa). Hence, researchers have resorted to ultracentrifuges, which are capable of generating psi approximate to 300 kPa. However, the volume of the soil mass used in these centrifuges is too small to be representative of field conditions and determination of moisture content of the soil specimen is done by invasive and destructive techniques. Under these circumstances, utility of electrical measurements (i.e., voltage across two points in the soil mass) for determining soil moisture content, which has the distinct advantage of being both nondestructive and noninvasive and facilitates development of the SWCC, seems to be quite promising. Validity of the technique has been demonstrated by comparing the resultant SWCC, for kaolin, vis-a-vis the SWCCs reported in the literature and those obtained from the pedo-transfer function (PTF). Further, unsaturated hydraulic conductivity (k(u)) of the kaolin was determined by employing various PTFs available in the SoilVision database and using the relationship proposed by Corey in 1977. It has been observed that the k(u) values obtained from these relationships match extremely well for psi <= 3000 kPa.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.001 | 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".