Science for art: multi-years' evaluations of biocidal efficacy in support of artwork conservation
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".