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Introduction à l’histoire des hôpitaux thermaux militaires en France (XVIIIe-XIXe siècles)

2010· book-chapter· fr· W2994808799 on OpenAlexaff
Gersende Piernas

Bibliographic record

VenuePresses universitaires du Septentrion eBooks · 2010
Typebook-chapter
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsArtHumanitiesPolitical science

Abstract

fetched live from OpenAlex

Le thermalisme militaire, soignant les soldats à l’eau minérale loin du front, remonte en France à l’Antiquité mais ce n’est qu’à l’époque moderne qu’il ressurgit. D’abord fâcheusement mêlé au thermalisme civil, il s’institutionnalise au XVIIIe siècle sous la forme de lieux de soins spécifiques pour atteindre son apogée au XIXe siècle : petits et grands hôpitaux thermaux militaires ou salles réservées dans les hôpitaux thermaux civils se partagent, le temps de courtes saisons, le territoire national et les malades, qui bénéficient d’une prise en charge de leurs soins par l’état. Un personnel médical militaire, certes saisonnier mais de plus en plus spécialisé, se met en place, prônant le système de la « cure surveillée », qui allie discipline et traitements thermaux. Cette médecine fait rapidement des émules tant civils que militaires, tant en France qu’en Europe, grâce à un enseignement et à une littérature prolixes. Les sources archivistiques subsistantes, peu nombreuses, permettent néanmoins de reconstituer cette histoire thermale militaire, les contours de cette population hospitalisée et les résultats médicaux qui demeurent mitigés.

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)0.001
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 score0.063
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.009
GPT teacher head0.172
Teacher spread0.164 · 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
Published2010
Admission routes1
Has abstractyes

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