Science for art: multi-years' evaluations of biocidal efficacy in support of artwork conservation
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
In recent decades, the relationship between Science and Art has been gradually strengthened through the use of diagnostic, conservation, and valorization technologies. New technologies can also be used to support the creation and durability of bio-artworks. Within such a context, starting from the Spring of 2014, we performed in situ experimentations to eventually increase the durability of the graphical artwork of William Kentridge on the Lungotevere embankments, whose creation was scheduled in the following years. We applied various combinations and concentrations of three different biocides (Algophase, Biotin R, and Preventol R80) and two water repellents (Hydrophase surfaces and Silo 111) on 34 test areas. However, the artist preferred to leave his artwork to a natural fading. Right before the realization of the graphical artwork “ Triumph and Laments of Rome” in 2016, just the black biological colonizations mainly composed of cyanobacteria were removed through pressurized water. We monitored the artist's work through analyses of images and colorimetric variations and such drawings showed a duration of 4 years in the natural conditions of recolonization. Here we show how the recolonization of treated and control areas, analyzed with the same methods, showed an increased duration, 3 years longer than under natural conditions in the case of Preventol R80 ® and Biotin R ® plus Silo 111 ® . The tested solutions showed differential effectiveness and multiple possibilities of use to support the maintenance of the artwork if the artist wanted to preserve his artwork for a longer period.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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