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Record W2018041665 · doi:10.1163/157338212x645094

Medical Translations and Practical Compilations: A Necessary Coincidence?

2012· article· en· W2018041665 on OpenAlexaff
Geneviève Dumas, Caroline Boucher

Bibliographic record

VenueEarly Science and Medicine · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsVernacularFifteenthContext (archaeology)Middle AgesPhenomenonClassicsAstrologyHistoryOrder (exchange)Middle EnglishLiteraturePhilosophyEpistemologyArtAncient history

Abstract

fetched live from OpenAlex

Fourteenth- and fifteenth-century medicine is characterised by a trickle-down effect which led to an increasing dissemination of knowledge in the vernacular. In this context, translations and compilations appear to be two similar endeavours aiming to provide access to contents pertaining to the particulars of medical practice. Nowhere is this phenomenon seen more clearly than in vernacular manuscripts on surgery. Our study proposes to compare for the first time two corpora of manuscripts of surgical compilations, in Middle French and Middle English respectively, in order to discuss form and matter in this type of book production.

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)0.007
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0050.020
Scholarly communication0.0140.008
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.059
GPT teacher head0.387
Teacher spread0.329 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2012
Admission routes1
Has abstractyes

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