A New Methodology for the Characterisation of Natural Dyes on Museum Objects Using Gas Chromatography–Mass Spectrometry
Bibliographic record
Abstract
The derivatising agent m-(trifluoromethyl)phenyltrimethylammonium hydroxide (TMTFTH) has been employed for more than a decade at the Canadian Conservation Institute (CCI) to extract natural dyes from historical textiles and other dyed substrates. The alkaline reagent breaks the bonds between the colourants and the mordant ions or functional groups of the substrate, releasing the dye compounds into the extraction solution, and derivatises polar functionalities to produce compounds that are amenable to subsequent analysis by gas chromatography–mass spectrometry (GC–MS). This approach allows for the identification of the colourants, and is also useful in determining the presence of degradation products from the dyes and substrates, non-dye marker compounds, auxiliary compounds added to the dye bath, and substances present on the object through anthropogenic use, conservation treatments, or possible pesticide contamination. This paper discusses compounds formed through the reactions of TMTFTH with flavonoid dyes (dyer’s buckthorn, old fustic, weld, red sandalwood, and brazilwood), quinone dyes (madder, Relbunium, Galium, cochineal, lac, and walnut), indigoid dyes (indigo, Tyrian purple, and indigo carmine), turmeric, marigold, lupin and several lichen species. Results from a selection of historical dyed textiles and other decorative objects analysed at the CCI are provided to illustrate applications of the methodology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".