Do not Dispose of Historic Fluid Collections: Evaluating Research Potential and Range of Use
Bibliographic record
Abstract
Abstract The use of specific preservative solutions by museum professionals to maintain fluid-preserved specimens has fluctuated over the years with advances in chemistry. The determining factors for the original choice of solution closely correlate with the historical parameters and original usage of the collections. Consequently, for any given collection, changes and substitutions over time in the types of preservative fluids used have likely occurred. The present comparative analysis of the state of brain preservation, carried out at macroscopic, microscopic, and molecular levels, allowed us to evaluate the effect of the different treatments applied over time to fluid-preserved collections. Our results confirm that the duration of formaldehyde exposure of the tissues clearly has an effect on their long-term preservation. Despite the controversies associated with the quality or use of some historic fixatives, modern analytical methods such as medical imagery reveal the preservation quality in historic specimens and their potential for future research use. However, the choice of fixatives and storage fluids to preserve the specimens is of critical importance because today's choices will influence the use of the specimen for advanced analytical methods in the future.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".