Evaluation of the performance of soil moisture sensors in laboratory-scale lysimeters
Bibliographic record
Abstract
Soil moisture sensors were evaluated in laboratory-scale lysimeters. The performances of tensiometers, granular matrix sensors (GMS), capacitance sensors, phase transmission sensors, and of a portable capacitance probe and a frequency-domain reflectometry (FDR) sensor was observed in loam (31.5% sand, 45.2% silt, and 23.1% clay) and silt loam (20% sand, 54% silt, and 26% clay) of the Ramada Series. The experiment was conducted over two drying cycles in loam for moisture contents decreasing from 34.0 to 17.0% by volume for the 1999 trial and decreasing from 43.1 to 20.0% by volume for the 2000 trial and over a single drying cycle in silt loam for moisture decreasing from 45.8 to 19.5% by volume. The lysimeters were designed with hydraulic weighing systems to facilitate continuous monitoring of the soil moisture content. A conversion equation was developed, based on texture-specific calibration curves published by the manufacturer, to calibrate the readings of the Aqua-Tel sensors. The procedure followed for converting the readings of the Aquaterr probe was also partially developed by the experimenter to obtain more accuracy. (Abstract shortened by UMI.)
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".