An analysis of the ground‐penetrating radar direct ground wave method for soil water content measurement
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Bibliographic record
Abstract
Abstract The spatial variability of soil water content can be measured with the ground wave velocity of ground‐penetrating radar (GPR) using short antenna offsets, but picking the correct ground wave arrival time is rather difficult. In applying the GPR ground wave method to soil water content estimation it is also important to know the effective sampling depth of the method. Uniform drainage experiments were conducted with 100 and 450 MHz GPR antennas using 1·0 and 2·0 m fixed antenna separations on a sandy loam soil to investigate time zero picking methodologies and to estimate the sampling depth of the GPR method. The GPR water content data were compared with time‐domain reflectometry (TDR)‐measured data using six vertical TDR probes of different lengths. Time zero was calculated from an air calibration at a 2·0 m antenna separation and from wide‐angle reflection and refraction data, and a difference was found between the two time‐zero calibration methods. A method was analysed to determine the arrival time of the leading edge of the direct ground wavelet using the arrival time of the peak amplitude, since the arrival time of the leading edge of the ground wave can be difficult to pick. Regression analysis showed that the GPR (100 MHz) measured water content was not different from the water content measured with TDR at 0–0·1 m depth, implying that this may be a reasonable estimate of the GPR ground wave method's sampling depth. A similar analysis based on the differences between the 0–0·2 m TDR and the GPR shows that the effective sampling depth of the direct ground wave of the 450 MHz data is less than the sampling depth of the 100 MHz data. Copyright © 2003 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it