Inference of vertical soil moisture distribution using high-frequency CMP and reflection traveltime analysis
Bibliographic record
Abstract
High-frequency ground-penetrating radar (GPR) surveys were used to investigate temporal water content variations in a vertical soil column characterized by stratified clean sand deposits over multiple annual cycles. Reflection profiling and common-midpoint (CMP) soundings were coincidently performed using 900 MHz antennas across a 2 m intensive monitoring profile. Our ability to identify fixed reflection events along a vertical soil profile permits inference of soil water flux across defined soil intervals in a non-invasive manner. Soil moisture contents were estimated from two-way traveltime measurements between seasonally coherent stratigraphic interfaces in the upper 2-3 m of soil. Interval thicknesses between stratigraphic interfaces were estimated from normal-moveout velocity analysis of coincidently collected CMP soundings. Interval traveltimes from reflection profiles were then converted to wave velocity using the interval thickness estimates and a volumetric water content estimate using an appropriate petrophysical relationship. The GPR effectively characterized long (e.g., seasonal trends) and short-period (e.g., distinct wetting events) variations in vertical soil moisture distribution.
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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 | 0.001 | 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".