Bibliographic record
Abstract
The Osteographia of William Cheselden (1688-1752) is universally recognized as one of the most important and beautiful books in the British anatomical tradition.1 Cheselden had two principal goals in creating the Osteographia: to provide the most accurate study of the human skeleton to date and to create the most attractive atlas of osteology available.By common agreement, he succeeded in providing a contender for both distinctions.Much has been written about the Osteographia and its place in the history of medicine, but little has been written about its engravings, which is surprising given that everyone who discusses the folio comments on their accuracy as illustrations and how striking they are artistically.My purpose in this paper is to begin a discussion of the engravings that at the same time places them within a larger epistemological and artistic context.Cheselden decided that it would be best to have his artists use a camera obscura to create the initial drawings for Osteographia.This decision would have seemed appropriate to him for a number of reasons bound up with the pursuit of precision and greater visual truth.The first half of the paper is devoted to the creation of the images.The second focuses on them as theoretical objects.In the second half I argue, by building a case on circumstantial considerations, that using a camera obscura creates viewing conditions that realize by analogy certain key doctrines of John Locke's epistemology, and that this could have implicitly, or even explicitly, influenced Cheselden's decision to use one.Creating a naturalistic representation of a complex object like a skull is a matter of artifice and convention (Figure 1).The principal trick is to render the three-dimensional world of experience-alive with light, colour and texture-into the two-dimensional world of black and white depiction.It is a testimony to the skills of an artist if this can be accomplished without the viewer commenting on the loss.In an engraving the artist creates the image
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".