Ageing Effects in Mounting Media of Microscope Slide Samples from Natural History Collections: A Case Study with Canada Balsam and PermountTM
Bibliographic record
Abstract
Microscope slide collections represent extremely valuable depositories of research material in a natural history, forensic, veterinary, and medical context. Unfortunately, most mounting media of these slides deteriorate over time, with the reason for this not yet understood at all. In this study, Raman spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, and different types of light microscopy were used to investigate the ageing behaviour of naturally aged slides from museum collections and the experimentally aged media of Canada balsam and Permount™, representing a natural and a synthetic resin, respectively, with both being based on mixtures of various terpenes. Whereas Canada balsam clearly revealed chemical ageing processes, visible as increasing colouration, Permount™ showed physical deterioration recognisable by the increasing number of cracks, which even often impacted a mounted specimen. Noticeable changes to the chemical and physical properties of these mounting media take decades in the case of Canada balsam but just a few years in the case of Permount™. Our results question whether or not Canada balsam should really be regarded as a mounting medium that lasts for centuries, if its increasing degree of polymerisation can lead to a mount which is no longer restorable.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".