Minerals provide tints and possible binder/extender in pigments in san rock paintings (South Africa)
Bibliographic record
Abstract
Abstract Minerals such as iron oxides and clays provide high tinting strength and improve the adhesive properties of pigments. In this study, we investigated the mineral composition of pigments from samples of San rock art. We used X‐ray diffraction and scanning electron microscopy to determine the mineral composition and micromorphology of pigments. Results showed that the major minerals in pigments in San rock art are whewellite, quartz, gypsum, hematite, and various alumino‐silicate minerals. The red hue in the pigment is due to hematite; gypsum and clays provide the white coloration, whereas black might be due to amorphous manganese compounds. We believe that whewellite with globular habit was extracted from plant sap (e.g., aloe vera) and added to the pigment, perhaps as binder, extender, or whitener. Whewellite with needle‐shaped morphology was present in cracks that developed in pigments and indicated an early stage of deterioration of the rock art. We propose that conservationists should seriously evaluate any change in the environmental conditions at the art site (e.g., removal of vegetation to improve touristic view) because such changes might significantly increase thermal fluctuations in pigments and promote crack formation and hence the decay of the San rock art. © 2008 Wiley Periodicals, Inc.
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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 | 0.001 | 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) | 0.002 | 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".