THREE DIMENSIONAL CHARACTERIZATION OF SOIL MACROPOROSITY BY X-RAY MICROTOMOGRAPHY
Bibliographic record
Abstract
Analysis of the soil pore system represents an important way of characterizing soil structure. Properties such as the shape and number of pores can be determined through soil pore evaluations. This study presents a three-dimensional (3D) characterization of the shape and number of pores of a sub-tropical soil. To do so, a second generation X-ray microtomograph equipped with a plain type detector was employed. A voltage of 120 kV and current of 80 mA was applied to the X-ray tube. The soil samples analyzed were collected at three different depths (0-10, 10-20, and 20-30 cm). The results obtained allowed qualitative (images) and quantitative (3D) analyses of the soil structure, revealing the potential of the microtomographic technique, as well as the study of differences in soil macroporosity at different depths. Macroporosity was 5.14 % in the 0-10 cm layer, 5.10 % in the 10-20 cm layer, and 6.64 % in the 20-30 cm layer. The macroporosity of unclassified pores (UN) was 0.30 % (0-10 and 10-20 cm) and 0.40 % (20-30 cm), while equant pores (EQ) had values of 0.01 % at the three depths under analysis.
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".