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Record W2949378741 · doi:10.7202/1064525ar

Médecins, chirurgiens, apothicaires : à qui sont adressées les traductions médicales ? Enquête sur l’édition lyonnaise des années 1540

2019· article· fr· W2949378741 on OpenAlexvenueno aff
Élise Rajchenbach

Bibliographic record

VenueRenaissance and Reformation · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsApothecaries' systemContext (archaeology)HumanitiesPolitical scienceLibrary scienceArtHistoryLawComputer science

Abstract

fetched live from OpenAlex

In the 1540s, medical publishing is in fashion in Lyon, specifically in the form of translations of Galen. Prefaces to the translations of the Greek physician highlight the conflicts underlying the practices of doctors, surgeons, and apothecaries in their closely-related disciplines. Translating Galen and his successors actually amounts to making accessible ancient science which was until then reserved for readers of Latin or Greek, that is to say, scholars. We study the issues that oversee the circulation of these translations as well as the receptions they enabled among a reading public much more diverse than it might seem, within a larger context of reflection on the role of translation as a vehicle for the dissemination of knowledge.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.024
Scholarly communication0.0130.005
Open science0.0010.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.002

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 head0.259
Teacher spread0.231 · 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 designQualitative
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

Citations0
Published2019
Admission routes1
Has abstractyes

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