Uncovering the Oppenheimer Siddur: using scientific analysis to reveal the production process of a medieval illuminated Hebrew manuscript
Bibliographic record
Abstract
Abstract The aim of this research was to use non-invasive scientific analysis to uncover evidence of the planning process and relationship between pigments used in text copying and artwork production in the Oppenheimer Siddur (Oxford Bodleian Library MS Opp. 776), an illuminated 15th-century Hebrew prayer book. In many medieval Hebrew illuminated manuscripts, the authorship of the artwork is unknown. This manuscript’s colophon states that it was copied by its scribe-owner for personal family use but does not confirm who was responsible for the artwork. Prior deductive analysis suggested that the scribe-owner may also have been the manuscript’s artist, based on common motifs and an apparent shared colour palette appearing in both texts and artwork. Visual examination using high resolution digital images also identified points of contact between pigments used in the manuscript’s texts and artwork, raising questions about the pigment application sequence, and concurrent versus sequential text copying and artwork production. An in-house developed remote spectral imaging system (PRISMS) with 10 filters spanning the spectral range from 400 to 880 nm was modified for close-range application to image two of the folios to examine the sequence of production, identify the pigments and compare the materials used for the illumination and the text. Optical microscopy and Fourier Transform Infrared spectroscopy in the attenuated total reflection mode (FTIR-ATR) were used directly on the folios to complement the spectral imaging data in binding media and pigment identification. The results revealed close matches in reflectance spectra for the colorants and inks used in both text copying and illuminations, suggesting that the same mixture of colorants and inks have been used. The spectral imaging in the near infrared bands revealed a hidden underdrawing, indicating a design change during production of the manuscript, and the outlining of letters prior to coloured pigment being applied. The pigment use, the variation in the binder for different pigments and some elements of its production were found to be consistent with those described in historical sources. The evidence from this study supports the hypothesis that the scribe applied pigments for the manuscript’s artwork at the same time he did some of the scribal work which has implications for understandings of Jewish medieval visual cultures.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".