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Record W7132262689

The Pigment Analysis of 18th Century Pastel Paintings by Maurice-Quentin de La Tour (1704-1788) and Jean Valade (1710-1787)

2016· article· en· W7132262689 on OpenAlexaff
Cécile Gombaud, David Buti, Johanne Marie Nielsen, Anna Vila

Bibliographic record

VenueMinistry of Culture Research Portal · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsCanadian Association of Thoracic Surgeons
Fundersnot available
KeywordsPaintingPortraitStudioWhite (mutation)PigmentPhotography
DOInot available

Abstract

fetched live from OpenAlex

Pastel paintings are rarely studied unless they are unframed [1-3]. The conservation treatment of three French pastel portraits by Maurice-Quentin de La Tour (1704-1788) and Jean Valade (1710-1787) at the paper conservation studio of the National Museum of Sweden gave the opportunity to study the materials, with a particular focus on pigments, used by the artists in the 18th century. The artworks analysed consisted of a preparatory drawing and two finished pastels. The pastel pigments can also be found on the backboard of one pastel. The aim of the analysis was to learn about the materials used by two of the leading pastellists of the time and, in order to outline their colour palette, characterize the white filler and the pigments used as well as the binders.<br/>The combination of photographic analysis, including UV and infrared photographs, together with different spectroscopic techniques allowed to characterize part of the artists’ palettes, both pigment and possible binding medium, and to have information about the paper support. <br/>After a first non-invasive campaign by means of X-rays fluorescence spectroscopy (XRF), which allowed an overall elemental investigation of the different coloured areas, invasive analyses were conducted on a number of selected micro-samples through Fourier transformed infrared (FTIR) and Raman spectroscopy. 18th century pastels often consist of several layers of paper or parchment, canvas and a strainer or a backing board. As a result, the interpretation of the XRF data are often complicated requiring further specific analysis.<br/>The results obtained combining photographic techniques, elemental and molecular analyses are shown here and deeply discussed and compared with literary sources, such as the contemporary treatise on pastel painting by Paul Romain de Chaperon (1732-1793) published in 1788 [4].<br/>Acknowledgements <br/>This project was supported by the Wiros Fund, Sweden.<br/>References <br/>[1] Norville‐Day, H. et al., The conservator, 1993. 17(1): p. 46-55.<br/>[2] Townsend, J.H., The Paper Conservator, 1998. 22(1): p. 21-2.<br/>[3] Sauvage, L. and Gombaud, C., CATS Proceedings II, 2014: p. 31-45.<br/>[4] Chaperon, P.R., Traite de la peinture au pastel, 1788.<br/>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.027
GPT teacher head0.305
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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