Conserving Transparent Plastics: Bringing Research into Practice Through the Treatment of the Poly(Methyl Methacrylate) Sculpture <i>Giraffa Artificiale</i>
Bibliographic record
Abstract
This paper presents the treatment of Giraffa Artificiale by Gino Marotta, a 3-meter-tall sculptural giraffe masterfully constructed in 1973 by shaping and assembling 67 pieces of transparent pink and colorless poly(methyl methacrylate) (PMMA). This sculpture, owned by Museo del Novecento in Milan, was in storage for over 20 years due to its poor condition; the work was covered by dust and scratches, one hoof and two tails were broken, and fragments were missing. Damaged artworks made of transparent plastics like Giraffa Artificiale are often kept in storage and not exhibited or deaccessioned from collections due to the lack of knowledge of how to successfully repair them and recover their transparency. The Getty Conservation Institute (GCI) recently completed extensive research to develop treatments to repair transparent plastics, particularly PMMA, and identified Giraffa Artificiale as an exemplary case study to put this research into practice. The conservation project was conducted by GCI in partnership with Museo del Novecento and Museum of Culture in Milan, and Centro Conservazione e Restauro La Venaria Reale in Turin. It included examination and documentation of technique and condition, materials characterization, testing of potential treatments, cleaning with agar spray, re-adhering broken pieces, filling scratches, chips, and cracks, and reconstructing missing fragments. Research findings were successfully applied, restoring the sculpture's transparency and intended form, and providing an example of how to bring these types of objects back to life.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".