Chronostratigraphic distribution and genesis of palygorskite in Tertiary sediments of the Isfahan region, central Iran
Bibliographic record
Abstract
Abstract No comprehensive study has yet been conducted to determine the chronostratigraphic distribution of palygorskite in the Tertiary sediments of Iran. Thirty sediment samples of different Tertiary epochs were taken, based on the field observations and geological maps. The clay fraction of samples was then investigated by X-ray diffraction (XRD), transmission and scanning electron microscopy (TEM and SEM), and inductively coupled plasma mass spectrometry (ICP-MS). Results showed that sediments of the Miocene and Pliocene had large amounts of palygorskite whereas no trace of this mineral was found in the sediments from the Palaeocene, Eocene and Oligocene. Geochemical analyses revealed that sediments younger than the Oligocene had greater amounts of soluble Mg and H4SiO4and a higher pH than those of the Palaeocene and Eocene. The stability diagram of the smectite-palygorskite system suggests that smectite is unstable and transforms to palygorskite in Neogene sediments. The SEM micrographs showed palygorskite as interwoven fibrous mats, coatings, pore-fillings and pore-bridging material in Neogene sediments. This textural evidence suggests a direct chemical precipitation of palygorskite by dissolution of silicates under the alkaline conditions. The results also suggest that geochemical conditions in the Early Tertiary era, represented by deep-sea conditions in central Iran, were not apparently favourable for palygoskite formation until the Late Oligocene.
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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 | 0.002 | 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) | 0.001 | 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".