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Record W2334304618 · doi:10.1177/1470357211408816

Illustrating Medicine: Line, Luminance and the Lessons from J.C.B. Grant’s <i>Atlas of Anatomy</i> (1943)

2011· article· en· W2334304618 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueVisual Communication · 2011
Typearticle
Languageen
FieldMedicine
TopicHistorical Medical Research and Treatments
Canadian institutionsUniversity of TorontoConcordia University
Fundersnot available
KeywordsLine drawingsAtlas (anatomy)Argument (complex analysis)Visual artsMedicineArtAnatomy

Abstract

fetched live from OpenAlex

The onset of the Second World War created a temporary crisis in the North American medical community when the supply of medical textbooks from Europe, used to train physicians and surgeons, was threatened. In 1941, Dr J.C.B. Grant of the University of Toronto proposed a new anatomical atlas, comprising both tonal and line drawings, to address this need. In this visual essay, the authors briefly illustrate Grant’s method for creating these drawings, and his systematic and deliberate use of photography in the process. They explain the reasons for Grant’s use of black and white images, and examine the specific illustration techniques used by these artists. A series of close-ups of the original drawings produced for the Atlas in the 1940s highlight the visual communication strategies deployed by these skilled illustrators. In so doing, they make an argument for the importance of examining how images are produced for medical publication, and not merely examining what is produced.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.395
Teacher spread0.300 · 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