Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the 19th century, arsenic was a commonly used additive and colourant found in paper, clothing, household goods, personal products, and even confectionary items. Although most of these toxic products have long been removed from public consumption, books created using copper acetoarsenite, a green pigment, remain in our libraries and personal collections, with potential health implications. This article focuses on identifying 19th-century books in the Queen’s University Library, Kingston, suspected to contain copper acetoarsenite or emerald green. Based on visual identification, 150 books published between 1797 and 1900 were selected from the collections for X-ray fluorescence (XRF) spectroscopy testing to detect the arsenical colourant. Results revealed that 28 books tested contained significant amounts of arsenic in their bookcloth, covering paper, surface decoration, endpapers, or fore-edges. These findings underscore the necessity to implement proper handling and storage protocols and conservation strategies to mitigate the risk of arsenic exposure to library staff, researchers, and patrons. Moreover, this research contributes to the broader understanding of arsenic’s impact on cultural heritage preservation, highlighting the importance of interdisciplinary collaboration between librarians, conservators, archivists, historians, and scientists. By documenting and addressing arsenic contamination in library collections, institutions can safeguard the well-being of individuals interacting with these materials while preserving these cultural heritage items for the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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