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Record W2948367124 · doi:10.1126/sciadv.aar6228

Pigment darkening as case study of In-Air Plasma-Induced Luminescence

2019· article· en· W2948367124 on OpenAlexafffund
M. Barberio, E. Skantzakis, S. Sorieul, P. Antici

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaDirectorate-General for Research and Innovation
KeywordsLuminescencePigmentPlasmaMaterials scienceChemistryOptoelectronicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

We introduce the use of an In-Air Plasma-Induced Luminescence (In-Air-PIL) spectroscopy as an alternative to classical chemical and crystallographic methods used in materials science. The In-Air-PIL is evaluated on a case study investigating the effect of light aging on the darkening of five pristine yellow pigments commonly used in artworks. We show that the darkening is not associated to changes in the chemical composition, but to a loss in crystallinity, indicating an amorphization process of the pigments induced and catalyzed by the light irradiation. This favors the interaction of the pigment molecules with oxygen and carbon adsorbed from the environment or solved in the binding agent, subsequently leading to the formation of oxalates and carbonates as observed in other works. We demonstrate that the In-Air-PIL results are in perfect agreement with more complex classical materials science analysis methods, making our plasma-driven method a potentially easier and faster technique.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.285
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations10
Published2019
Admission routes2
Has abstractyes

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