Pigment darkening as case study of In-Air Plasma-Induced Luminescence
Bibliographic record
Abstract
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.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".