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Record W3030808407 · doi:10.1186/s40494-020-00382-3

Salvator Mundi: an investigation of the painting’s materials and techniques

2020· article· en· W3030808407 on OpenAlexfundno aff
Nica Gutman Rieppi, Beth Price, Ken Sutherland, Andrew P. Lins, Richard Newman, Peng Wang, Ting Wang, Thomas J. Tague

Bibliographic record

VenueHeritage Science · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
FundersYork University
KeywordsPaintingCinnabarMineralogyArtMaterials scienceChemistryArt historyHematite

Abstract

fetched live from OpenAlex

Abstract Before the start of its restoration in 2007, the Salvator Mundi was thought to be one of a number of copies of a long-lost Leonardo da Vinci painting, depicting Christ giving a blessing with his right hand while holding a crystal orb in his left. During the restoration treatment, a scientific examination of the painting was carried out to elucidate the painting’s materials and techniques. Microscopic sampling of the painting was necessarily limited, and nine out of ten samples were prepared and analyzed as cross-sections. A number of analytical methods were employed selectively, including stereomicroscopy, visible and fluorescent light microscopy, scanning electron microscopy with energy dispersive spectroscopy, Raman microspectroscopy, Fourier transform infrared microspectroscopy in transmission mode and with attenuated total reflection. The pigments characterized were lead white, vermilion, red iron oxide earth, red lake, natural ultramarine, lead–tin yellow, umber, and charcoal, carbon and bone blacks. Manganese-containing soda-lime glass was detected in the ground, imprimitura and paint layers, and a walnut oil medium was identified by pyrolysis gas chromatography-mass spectrometry. Cross-section studies revealed aspects of the painting’s stratigraphy: a size layer, white ground and off-white imprimitura, followed by a complex sequence of paint layers applied by the artist to achieve sophisticated visual effects.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.046
GPT teacher head0.232
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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