The first Raman spectroscopic study of San rock art in the Ukhahlamba Drakensberg Park, South Africa
Bibliographic record
Abstract
Abstract San rock art sites are found throughout southern Africa; unfortunately this unique heritage is rapidly being lost through natural weathering processes, which have been the focus of various studies conducted in the uKhahlamba Drakensberg Park since 1992. It has recently been shown that the ability of Raman spectroscopy to identify salts on rock faces on a micro, as well as nano scale, can make a contribution to these projects. In order to test the feasibility of undertaking on‐site analyses, a small rock fragment with red and white pigments still attached, which had weathered off the rock face, was analysed with Raman spectroscopy under laboratory conditions, using a Dilor XY Raman instrument and a DeltaNu Inspector Raman portable instrument. A small sample of black pigment (<1 mm2), collected from a badly deteriorated painting and a few relevant samples collected on site, were analysed as well. It was possible to identify most of the inorganic pigments and minerals detected with previous XRD and EDX measurements including whewellite and weddellite coatings, which could be a tool for carbon dating purposes. Two carotenoid pigments were detected for the first time in San rock art pigments. Animal fat was also observed for the first time on both red and white pigments, on the rock face adjacent to the paintings and in highest concentrations on the back of the rock fragment. The spectra quality makes successful on‐site measurements a good prospect. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.002 | 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) | 0.002 | 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".