Deterioration-associated microbiome of a modern photographic artwork: the case of Skull and Crossbones by Robert Mapplethorpe
Bibliographic record
Abstract
Abstract The preservation of cultural heritage, including ancient photographic materials, is of paramount importance in the field of conservation science. In this context, the microbial diversity of ‘Skull and Crossbones’, a 1983 photograph by Robert Mapplethorpe printed on silver gelatine, was assessed. We employed both culture-dependent and culture-independent methods to characterize microbial communities inhabiting this artwork. Vibrational Raman micro spectroscopy and FT-IR spectroscopy were utilized to assess the chemical degradation condition and characterize the chemical components of the silver gelatin print. The combination of molecular sequencing methods (Sanger and HTS approach) and non-invasive vibrational spectroscopy yielded valuable insights into the microbial communities thriving on photographic material and the chemical degradation of the print. Isolated fungal strains were added to the Fungal Collection at the University of Naples Federico II, and their deteriorative potential was investigated by adding substrates, commonly used in canvas photographs to the culture media. These results establish a link between microbial communities colonizing ancient photographic materials, paper decomposition, and the enzymatic patterns of the retrieved microorganisms. This information is invaluable for understanding and addressing biodeterioration progression on valuable works of art, such as historical photographs, which remain understudied.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".