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Record W3202451439 · doi:10.4000/books.cths.15775

Présence des drogues d’origine animale dans la pharmacopée charitable au xviie siècle : l’exemple des Secrets touchant la médecine

2021· book-chapter· fr· W3202451439 on OpenAlexaff
Olivier Lafont

Bibliographic record

VenueÉditions du Comité des travaux historiques et scientifiques eBooks · 2021
Typebook-chapter
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsCanadian Society for the History of Medicine
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

In his tribus versantur était la devise des apothicaires qui traduisait le fait que les drogues utilisées pour préparer les médicaments provenaient des trois règnes de la nature : animal, végétal et minéral. Il s’agissait là de la médecine officielle qui découlait des dogmes enseignés dans les facultés à Paris ou Montpellier. La part qu’occupaient les substances animales dans la médecine populaire est difficile à évaluer ; il existe peu de traces écrites. Un moyen d’accéder au contenu de la médecine charitable est, en revanche, offert par des ouvrages rédigés pour des personnes charitables dans le but de les aider à prendre en charge la santé des pauvres. Certains de ces ouvrages, dus à des médecins ou des personnes cultivées, s’appuyaient trop sur la science officielle pour pouvoir éclairer la médecine populaire. En revanche, un petit livre intitulé Secrets touchant la médecine se montre plus proche de la pratique populaire. L’étude des formules de remèdes qu’il propose permet d’évaluer la part des drogues animales que l’on peut ensuite interpréter à l’aide des pharmacopées savantes.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.040
GPT teacher head0.256
Teacher spread0.217 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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