At the Core of the Workshop: Novel Aspects of the Use of Blue Smalt in Two Paintings by Cristóbal de Villalpando
Bibliographic record
Abstract
During the seventeenth century, the use of smalt and indigo became increasingly common among painters’ workshops in New Spain. The unprecedented importance of these two blue pigments in oil painting may be explained by artistic and geopolitical circumstances. This article expands on the use of blue smalt—a byproduct of glass production and a material that lacks in-depth study in viceregal painting—by focusing on the technical analysis of El Triunfo de la Eucaristía and La Asunción painted by Cristóbal de Villalpando (ca. 1649–1714), which are part of the collection of the Museo Regional de Guadalajara (Mexico). The technological and material study of both paintings, situated within the trade and circulation of painting materials at the turn of the eighteenth century, shows how the painter deployed techniques rooted in his predecessors while incorporating particular technical adaptations. The authors examine cross-section samples of Villalpando’s paintings with optical microscopy, Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), and Fourier-transformed infrared spectroscopy (FT-IR), and were able to identify different qualities of smalt as well to suggest a possible provenance. These analyses evidence novel aspects in the painting tradition of workshops in New Spain that ultimately reverberated in practices of the long eighteenth century.
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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 | 0.001 | 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 | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".