MétaCan
Menu
Back to cohort
Record W3015129365 · doi:10.7202/1068273ar

Ce que la lettre familière fait au discours médical. Une lecture de la lettre XIX, 16 des Lettres de Pasquier (1619)

2020· article· fr· W3015129365 on OpenAlexvenueno aff
Benoît Autiquet

Bibliographic record

VenueArborescences Revue d études françaises · 2020
Typearticle
Languagefr
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

L’article porte sur la lettre XIX, 16 du second tome desLettresde Pasquier, publié en 1619. Cette lettre, qui traite de la science médicale de l’époque de l’auteur, est généralement lue comme un lieu où Pasquier, refusant les dogmes médicaux au nom du scepticisme, fait valoir la vérité de l’expérience personnelle en matière médicale. Nous essayons de montrer au contraire que, loin de valoriser uniquement le savoir individuel, cette lettre, très critique envers les dogmes médicaux, propose néanmoins des formes institutionnelles du savoir médical. Mais celles-ci, contrairement aux « écoles » antiques, ne sont pas construites autour d’un centre dogmatique. Deux modèles institutionnels, concurrents et parfois contradictoires, sont proposés par l’auteur : un modèle divin, qui fait des médecins des agents de Dieu ; un modèle humain, où les médecins ont le rôle de « compilateurs » des remèdes locaux qui, conformément à la théorie médicale des climats, sont les seuls à pouvoir soigner les habitants d’un lieu. On propose, en fin de parcours, une tentative pour articuler ces deux modèles.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.018
Scholarly communication0.0060.008
Open science0.0010.004
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0210.006

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 head0.260
Teacher spread0.238 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueArborescences Revue d études françaisesSame topicHistorical and Scientific StudiesFrench-language works237,207