Three‐Dimensional Sensitivity Distribution and Sample Volume of Low‐Induction‐Number Electromagnetic‐Induction Instruments
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Bibliographic record
Abstract
There is an ongoing effort to improve the understanding of the correlation of soil properties with apparent soil electrical conductivity as measured by low‐induction‐number electromagnetic‐induction (LIN FEM) instruments. At a minimum, the dimensions of LIN FEM instruments' sample volume, the spatial distribution of sensitivity within that volume, and implications for surveying and analyses must be clearly defined and discussed. Therefore, a series of numerical simulations was done in which a conductive perturbation was moved systematically through homogeneous soil to elucidate the three‐dimensional sample volume of LIN FEM instruments. For a small perturbation with electrical conductivity similar to that of the soil, instrument response is a measure of local sensitivity (LS). Our results indicate that LS depends strongly on the orientation of the instrument's transmitter and receiver coils and includes regions of both positive and negative LS. Integration of the absolute value of LS from highest to lowest was used to contour cumulative sensitivity (CS). The 90% CS contour was used to define the sample volume. For both horizontal and vertical coplanar coil orientations, the longest dimension of the sample volume was at the surface along the main instrument axis with a length of about four times the intercoil spacing (s) with maximum thicknesses of about 1 and 0.3 s, respectively. The imaged distribution of spatial sensitivity within the sample volume is highly complex and should be considered in conjunction with the expected scale of heterogeneity before the use and interpretation of LIN FEM for mapping and profiling.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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