VERTICAL SOIL PROFILING USING A GALVANIC CONTACT RESISTIVITY SCANNING APPROACH
Bibliographic record
Abstract
Site-specific crop productivity is heavily influenced by the ability of soil to store water and nutrients while still permitting excess water to drain. One of the most promising practices to define spatial soil heterogeneity in terms of physical characteristics is the application of electrical conductivity/resistivity maps. The instruments used to map such soil characteristics use galvanic contact and capacitive coupling resistivity measurements as well as electromagnetic induction. Despite the type of instrument, the geometrical configuration between signal transmitting and receiving elements defines the shape of the depth response function. To assess vertical variation of soils from the surface, many modern instruments use multiple transmitter-receiver pairs to record electrical conductivity/resistivity signals applicable to different soil depths. Alternatively, vertical sounding methods can be used to measure a change in apparent soil electrical conductivity with the depth at a specific location. This paper examines the possibility for dynamic assessment of soil profiles using a surface galvanic contact resistivity scanning approach, with transmitting and receiving electrodes configured in an equatorial dipole-dipole array. An automated scanner system has been developed and tested in the agricultural field environment with different soil profiles. While operating in the field, the distance between current injecting and measuring pairs of rolling electrodes was varied continuously from 40 to 190 cm. The resulting scans were evaluated against 1-m deep soil profiles and that of an electromagnetic induction instrument at various depths.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".