DIVERSITY OF CLAY MINERALS IN THE VERTISOLS OF THREE DIFFERENT CLIMATIC REGIONS IN WESTERN IRAN
Bibliographic record
Abstract
Considerable information exists in the literature showing that expansive layer silicates are not the only clay minerals present in vertisols. However, the presence of a very high clay content dominated by fine clay, regardless of the clay type, together with the wetting and drying cycle in the soil can also produce a high shrink-swell potential. We studied some vertisols with diverse parent materials and climates from western Iran to investigate the role of parent material and climate on formation of these soils. The vertisols of Fars Province (Southwest Iran) have formed on calcareous sediments with ustic-hyperthermic soil moisture and temperature regimes and a mineralogical composition dominated by a palygorskite-chlorite suite. The vertisols of Lorestan Province (Midwest Iran) are also formed from calcareous sediments under the xeric moisture and thermic temperature regime, and contain vermiculite as the dominant clay mineral. In Kermanshah Province, vertisols have formed on limestone or in calcareous sediments. They have xeric-thermic soil moisture and temperature regimes. In Ardebil Province, vertisols are formed on volcanic sediments, and they have xeric-mesic soil moisture and temperature regimes. All vertisols, except those from Fars Province, are classical ones and include montmorillonite in the clay fraction. Our study shows that the interparticle pore size that is controlled by the size of primary particles, regardless of its nature, contributes to the shrink-swell potential in the soils we studied in Iran.
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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 | 0.001 | 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 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".