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Record W4307226477 · doi:10.1098/rsnr.2022.0020

Nehemiah Grew, the illustrator

2022· article· en· W4307226477 on OpenAlexfundno aff
Pamela Mackenzie

Bibliographic record

VenueNotes and Records the Royal Society Journal of the History of Science · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHistoryFeature (linguistics)Art historyVisual artsClassicsArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

The literature on seventeenth-century Royal Society member Nehemiah Grew's artistic production has been sparse and tentative. Although his publication record includes five illustrated books, some of which feature quite elaborate illustrative programmes, it has been challenging to credit any of this visual production directly to the books’ author. In this article, I aim to both contribute to the growing interest in Grew's illustrations, and to provide a corrective to this gap in the literature, presenting Grew for the first time as an active illustrator and arguing for the importance of Grew's visual production during his career with the Royal Society. I will discuss his visual archive and his relationship with his engravers and will also present evidence of his regular use of illustrated figures in lectures he presented throughout the 1670s. This includes attributing two original drawings to Grew that are still present in the Royal Society's collections—two dissected cat's kidneys—that are associated with a lecture he gave on animal anatomy in 1679.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.015

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 head0.022
GPT teacher head0.196
Teacher spread0.174 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNotes and Records the Royal Society Journal of the History of ScienceSame topicHistorical Art and Culture StudiesFrench-language works237,207