Long-Term Storage of Small Natural History Specimens Using Gelatin Capsules: A Case Study from the Royal Alberta Museum
Bibliographic record
Abstract
Abstract Museums use gelatin capsules to store small objects and specimens, despite limited documentation of their long-term viability. The Royal Alberta Museum (RAM of Canada) uses gelatin capsules to store seeds, bones, and plant material because of their ease of use, transparency, soft-bodied walls, size availability, and low cost. Recently, RAM staff reported damaged capsules from the palaeontology collections. We evaluated 499 capsules used to store specimens accessioned in 1986 and 1988 and investigated capsule properties using Fourier transform infrared spectroscopy and Oddy testing. Only 4.21% of inspected capsules were dented, cracked, and/or fractured. Based on interviews and testing, we determined that damage to capsules likely resulted during handling (i.e., applied force when opening). We conclude that gelatin capsules offer a good, inexpensive method for long-term storage of small, dried specimens in environmentally controlled conditions. Alternatives to gelatin capsules exist, although their pros and cons require evaluation before use. All storage methods require continuous monitoring for signs of container or specimen deterioration.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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 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".