Conservation process of water-damaged herbarium specimens at the Harvard University Herbaria
Bibliographic record
Abstract
In December 2009, following an upgrade of the Harvard University Herbaria's heating and cooling system, a pipe burst in one room, resulting in the soaking of specimens in the adjacent cases. The soaked specimens were removed, and the degree of water damage was assessed. The saturated specimens were placed in plastic bags and immediately transferred to a walk-in freezer set at −20°C. Slightly wet specimens were spread out to air dry. Restoration of the frozen specimens involved tests to determine the most effective method for restoring them to usable condition. Test specimens of no scientific value were intentionally soaked, then dried using two procedures: (1) silica gel desiccation and (2) vacuum freeze drying. Freeze-dried specimens did not adhere to each other as much as did those that were dried with silica gel and was the method chosen. Upon their return, the dried specimens were sorted into groups: (1) those that were immediately ready to be returned to the collection, (2) those requiring minor repair, such as reattaching detached labels or plant parts, and (3) those requiring major repair. All specimens were annotated to indicate that they were water damaged and the method of restoration used and then they were returned to the collection.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".