Comparison of Preventive Conservation Guidelines for Particulate Matter and Lighting in Heritage Libraries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The opportunity left by the COVID-19 lockdown gave institutions time to evaluate the impact of tourism on historical museums. However, the lack of a comprehensive analysis of the current conservation guidelines for lighting and particulate matter makes its assessment not so straightforward. Therefore, the present gap was addressed by reviewing and discussing preventive conservation guidelines for those two parameters and their application. Guidelines’ approaches were compared by evaluating the monitoring data in two historic libraries. Illuminance and particulate matter were measured before and during the lockdown to determine how tourism affected measurement results. While there are sufficient guidelines for lighting, there is a need to develop guidelines that assess and mitigate problems concerning particulate matter in cultural collections. Moreover, almost all guidelines were sensible to the operational changes introduced during the lockdown, of which two were considered more suitable for use in historic libraries. The direct relationship between tourism and particulates was reported (at least 28% reduction), while an indirect impact was observed (59% reduction) for lighting. In case of poor metrics compliance, the present study proposes an action plan based on literature findings for each parameter to address a compromise between tourism and collections preservation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 it