MétaCan
Menu
Back to cohort
Record W3208167042 · doi:10.3138/cbmh.474-102020

Pigmented Remedies: The Pharmacy of Colour in Early Modern Europe

2021· article· en· W3208167042 on OpenAlexvenueno aff
Julia Nurse

Bibliographic record

VenueCanadian Journal of Health History · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsApothecaries' systemEarly modern periodPharmacyPeriod (music)ReceiptLate 19th centuryTraditional medicineHistoryVisual artsArtMedicineAncient historyAestheticsPolitical scienceFamily medicineLaw

Abstract

fetched live from OpenAlex

This article will examine pigments recently identified in an unpublished conservation survey at the Wellcome Collection that included two 17th-century medical manuscripts. These pigments, which were drawn from plant and mineral products, served a dual purpose based on their medicinal and pigmented properties. An exploration of how these pigments were used (and why) by a range of practitioners – including apothecaries, physicians, “kitchen physicians,” and artisans – reveals the importance of colour throughout early modern Europe. The persistence of traditional medical theories is revealed by examining evidence across an extensive period covering the 16th to the 18th century. Receipt books, medical treatises, and health guides are contrasted with artisanal texts reflecting the blurring of boundaries between the worlds of medicine and art. Modern analysis by conservators of colour used in medieval and early modern texts is crucial to the preservation of pigments but also provides a deeper understanding of what and how pigmented products were used in the period and, ultimately, informs our current understandings of early modern life and medicine.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.009
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.091
GPT teacher head0.252
Teacher spread0.161 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Health HistorySame topicCultural Heritage Materials AnalysisFrench-language works237,207