Insights From the NANOforArt Project: Application of Calcium-Based Nanoparticle Dispersions for Improved Preservation of Parchment Documents
Bibliographic record
Abstract
Abstract Following pilot testing of the effects of alkaline-based nanoparticles on modern parchment, the treatment was extended to historical parchment. This paper describes the application and impact of calcium hydroxide and calcium carbonate nanoparticles dispersed in (i) propan-2-ol and (ii) cyclohexane on a parchment book cover dated 1570. The cover showed signs of damage resulting from contact with iron gall inks and low pH values (∼4–5). Protocols for the damage assessment of collagen in parchment as developed in the IDAP project (Improved Damage Assessment of Parchment) were used to evaluate the impact of the conservation treatments on parchment. Preliminary results have shown that the application of calcium-based nanoparticles did not produce any adverse effects on the state of preservation of collagen. In addition, positive outcomes emerged: the pH was re-adjusted to a neutral value, a strengthening and consolidation effect was observed, and the nanoparticles exhibited a protective action upon artificial ageing of the treated parchment.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".