Toxicity in 3D: XRF Analysis for the Presence of Heavy Metals in a Historical Stereograph Collection at Queen’s University Library, Canada
Why this work is in the frame
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Bibliographic record
Abstract
This study employs non-destructive X-ray fluorescence (XRF) spectroscopy to identify the presence of potentially harmful heavy metals in a collection of nineteenth century stereographs housed at W.D. Jordan Rare Books and Special Collections at Queen’s University in Kingston, Ontario, Canada. Stereographs were extremely popular forms of entertainment and education in the Victorian era. As a result, they are common in archives, libraries, galleries, museums, and personal collections alike. This article provides an introduction to the history of stereographs, a background on their production, and pXRF analysis into the composition of pigments present on the stereograph mounts. Sixty-nine stereographs were selected for pXRF analysis, dating between 1852 and 1940, with the majority of the stereographs dating prior to 1895. Many of these cards are brightly coloured in greens, oranges, yellows, and pinks. Research revealed that arsenic-based pigment was common among all green stereograph cards analysed, lead-based pigment was common among all orange stereograph cards analysed, and lead- and chromium-based pigments were common among all the yellow cards analysed. However, additional analytical techniques need to be employed for definitive pigment identifications. This study demonstrates that hazardous pigments from the nineteenth century extend beyond wallpapers, books, and textiles and are likely to be pervasive in many heritage workplaces. This research highlights the importance of educating staff who work with archival collections. Understanding the scope of toxic pigments in archival collections is critical to ensuring proper handling, storage, and mitigation strategies to protect both the health of individuals and the integrity of these historically significant artifacts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it