Rembrandt as a Painter: New Technical Research. Introduction
Bibliographic record
Abstract
This article provides an introduction to this special issue of ArtMatters presenting essays developed from the online international symposium New Technical Research on Rembrandt: Paintings, Drawings, Prints organised by the Städel Museum, Frankfurt, in January 2022. Focusing on paintings, seven papers report on recent technical investigations of works by Rembrandt and his studio in the collections of the Städel Museum; the Agnes Etherington Art Centre, Queen’s University, Kingston, Canada; the Ashmolean Museum, Oxford; the Gemäldegalerie Alte Meister, Hessen Kassel Heritage; the Gemäldegalerie, Staatliche Museen zu Berlin; the Hessisches Landesmuseum, Darmstadt; the Mauritshuis, The Hague; and the National Gallery of Art, Washington, DC. Co-authored by art historians, conservators and scientists, these essays explore how current technologies and methods can shed new light on Rembrandt’s painting techniques and workshop practice while pointing the way to future research. This introduction summarises key themes and discoveries that tie these studies together.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".