Use of the Geonics EM‐38 to Delineate Soils in a Loess over Till Landscape, Southwestern Iowa
Bibliographic record
Abstract
Soil electrical conductivity (EC) has shown promise as a means of obtaining rapid, inexpensive soils information in the American Midwest. Therefore, instruments that measure soil EC have received a considerable amount of attention in the literature. However, there are still a number of important soil associations that have not been investigated with EC techniques. Loess‐derived soils make up a considerable portion of the soil area in Iowa, but have received little to no attention from those investigating EC as a soil mapping tool. This study investigates soil EC and its relationship to the soils of the loess‐derived Marshall‐Exira soil association in southwestern Iowa through use of a Geonics EM‐38 (Geonics Ltd., Mississauga, ON, Canada) linked to a Trimble GPS unit (Trimble, Sunnyvale, CA) and towed at slow speed through two fields on a nonconductive trailer. Resulting EC values were mapped using SURFER software (Golden Software Inc., Golden, CO) and compared with soil delineations from Order 1 soil surveys for the two fields. The EM‐38 performed well in detecting soils derived from paleosols, but was less useful for differentiating other soils in the fields. The lack of distinct EC values for most of the soils in the field may have been due to low soil water content following a very dry and warm spring, as soil EC values have been shown to converge as soils dry. The ability of the EM‐38 to differentiate paleosol‐derived soils from the surrounding loess, till, alluvium, and colluvium‐derived soils, even in the dry conditions present when data was collected for this study, could prove valuable in soil mapping applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".