Measurement of Low Matric Potentials with Porous Matrix Sensors and Water‐Filled Tensiometers
Bibliographic record
Abstract
Water‐filled tensiometers are widely used to measure the matric potential of soil water. It is often assumed that, because these give a direct reading, they are accurate. With a series of laboratory tests with model laboratory systems of increasing complexity we show that the output of water‐filled tensiometers can, particularly in drying soils, be in serious error. Specifically, we demonstrated that water‐filled tensiometers can indicate a steady matric potential, typically between −60 and −90 kPa, when the soil is much drier. We demonstrate the use of water‐filled tensiometers that can measure matric potentials smaller than −100 kPa in the laboratory and in the field. The physics of the failure of water‐filled tensiometers is discussed. When the matric potential was greater than −60 kPa, in laboratory and field tests water‐filled and porous matrix sensors were in good agreement. In the field environment the porous matrix sensor was useful because it allowed early detection of the failure of water‐filled tensiometers. In dry soils (matric potential < −60 kPa) the porous matrix sensor was more reliable and accurate than the water‐filled tensiometer.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".