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Record W2410076760

Robert Carswell: the first illustrator of MS.

2009· article· en· W2410076760 on OpenAlexaff
Murray Tj

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicinePaintingArt historyBiographyQueen (butterfly)Art
DOInot available

Abstract

fetched live from OpenAlex

The first illustration of multiple sclerosis (MS) was by a young Scottish physician and artist, Dr Robert Carswell. Recognized as a talented illustrator by his teachers, he was encouraged to create an anatomy and pathology atlas. He spent years in the hospitals and mortuaries of Paris and Lyon painting watercolours and pen and ink drawings of patients and post mortem preparations. Of the 1034 paintings, 99 are of the brain and spinal cord and Plate 4, figure 4.4 in the atlas (Figure 2), is of MS. Carswell indicated he saw two examples of this pathology, but had not examined either patient, but illustrated one of them. We know little about the clinical history other than that the patient was paralyzed. About 200 of the atlases were printed, and it is still regarded as one of the greatest and most beautiful of all medical books. Carswell was appointed as the first Professor of Anatomy at the North London Hospital, later renamed the University College Hospital UK, where the original copy of his great atlas is archived. Due to ill health he resigned after a few years to reside in the healthier air outside Brussels, Belgium. He was appointed physician to King Leopold, but was also noted for his care of the poor. Queen Victoria knighted him for his care of King Louis Philippe of France when he was in exile. Although English journals did not note his passing at the age of 64 years, his great atlas remains as his memorial.

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)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0860.051

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 head0.028
GPT teacher head0.231
Teacher spread0.204 · 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
GenreOther

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

Citations5
Published2009
Admission routes1
Has abstractyes

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