Measurement of electrical conductivity of pore water in saturated sandy soils using time domain reflectometry (TDR) measurements
Bibliographic record
Abstract
Studying solute transport in soils is hampered by a lack of technology for continuously monitoring ionic concentration of contaminants. The electrical conductivity of pore water is a strong indicator of ionic concentration of contamination in soil. Using the bulk electrical conductivity of a soil measured by time domain reflectrometry (TDR) to predict the soil pore-water electrical conductivity appears to be a promising technique. This study presents a new method for estimating the pore-water electrical conductivity of saturated sandy soils using a single TDR test. The effects of pore-water electrical conductivity, temperature, porosity, and ionic types on the electrical conductivity of soil were studied. An average value of the exponent in the Archie’s Law was found to be 1.457 for the saturated sandy soils used in this study. A laboratory model infiltration test was also conducted with continuous monitoring of the electrical conductivity of the pore water by TDR. The results showed that TDR is able to provide a reasonably accurate estimation of the electrical conductivity of pore water. Consequently, it may be possible to monitor the in situ ionic contamination in saturated sandy soils using TDR technology.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".