Application of X-ray computed tomography to soil science: A literature review
Why this work is in the frame
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Bibliographic record
Abstract
The study of the spatial configuration of soil, in its complexity, requires an understanding of the interrelations and interactions between the diverse soil constituents, at various levels of organization. Investigations of the spatial arrangement of the mineral and organic components of soil have benefited from the development of techniques for structural analysis. X-ray computed tomography (CT) is a non-destructive and non-invasive technique that has been successfully used for three-dimensional (3D) examination of soil. Valuable information has been obtained by the application of CT for the description and quantitative measurements of soil structure elements, especially of soil pores and pore network features. In many studies, X-ray CT has been used to investigate the hydro-physical characteristics of the soil, in a functional and temporal manner. A dynamic approach has also been utilized in the evaluation of the biotic factor influence on soil. The analysis of soil solid phases, by X-ray CT, has been challenging due to the similar X-ray attenuation of different solid constituents. However, the use of multiple X-ray energy levels has facilitated the discrimination of minerals in soil. The aim of this review and synthesis is to offer a perspective on the major issues related to application of the technique, general attempted solutions and possible directions in the utilization of X-ray CT in soil research. Relevant scanning parameters, procedures for CT image reconstruction, algorithms for the quantification of soil characteristics and results are presented for each type of application. Key words: X-ray computed tomography, energy level, spatial resolution, segmentation, soil mineral and organic constituents, soil physical and hydro-physical properties, soil biota
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it