Characterizing arsenic in preserved hair for assessing exposure potential and discriminating poisoning
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
Advanced analytical techniques have been used to characterize arsenic in taxidermy specimens. Arsenic was examined to aid in discriminating its use as a preservative from that incorporated by ingestion and hence indicate poisoning (in the case of historical figures). The results are relevant to museum curators, occupational and environmental exposure concerns, toxicological and anthropological investigations. Hair samples were obtained from six taxidermy specimens preserved with arsenic in the late 1800s and early 1900s to investigate the arsenic incorporation. The presence of arsenic poses a potential hazard in museum and private collections. For one sample, arsenic was confirmed to be present on the hair with time-of-flight secondary ion mass spectrometry and then measured with neutron activation analysis to comprise 176 microg g(-1). The hair cross section was analysed with synchrotron micro-X-ray fluorescence to investigate the transverse distribution of topically applied arsenic. It was found that the arsenic had significantly penetrated all hair samples. Association with melanin clusters and the medulla was observed. Lead and mercury were also identified in one sample. X-ray absorption near-edge spectroscopy of the As K-edge indicated that an arsenate species predominantly existed in all samples; however, analysis was hindered by very rapid photoreduction of the arsenic. It would be difficult to discriminate arsenic consumption from topically applied arsenic based on the physical transverse distribution. Longitudinal distributions and chemical speciation may still allow differentiation.
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 | 0.001 | 0.001 |
| 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