Preferential Solute Flow in Intact Soil Columns Measured by SPECT Scanning
Bibliographic record
Abstract
Single photon emission computed tomography (SPECT) is an imaging technique that is widely used in medical diagnosis. This technique has never been applied to soils. The objective of this study was to investigate the capabilities of SPECT scanning for visualizing preferential flow in soil. This paper describes the principle of SPECT scanning and its application to tracer breakthroughs in four large undisturbed soil columns (800‐mm length × 77‐mm diam.). This new approach allows real‐time analysis of flow patterns of radioactive tracers in 2‐D using planar imaging, and in 3‐D using the tomographic capabilities of the SPECT scanner. Not only does SPECT scanning provide qualitative data, but it also allows for the quantification of a tracer's spatial distribution. Our results characterized preferential flow very clearly in soil columns. SPECT scanning opens up new avenues for 2‐D and 3‐D tracer studies in porous media such as soils.
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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 | 0.000 |
| 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) | 0.001 | 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 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".