MétaCan
Menu
Back to cohort
Record W2411344081

[The epidemic typhus of 1813/14 in the area of lower Franconia].

2004· article· en· W2411344081 on OpenAlexaboutno aff
Manfred Vasold

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsnot available
Fundersnot available
KeywordsTyphusBattleGermanQuarter (Canadian coin)Epidemic diseaseHistoryFellAncient historyDemographyGeographyMedicineCartographyVirologyArchaeologySociology
DOInot available

Abstract

fetched live from OpenAlex

When Napoleon left for Moscow, in June 1812, he marched at the head of a huge army, perhaps more than half a million men strong. Roughly one fifth of them survived and came back to Germany at the turn of 1812/13. The "Grande Armée" had been subject to open battles and guerilla warfare, but even more to the ravages of hunger and infectious disease - it was epidemic typhus that killed off the soldiers. On their way back to France, the soldiers carried that disease to some areas of Germany, esp. those along the Main river. In late winter of 1813 some parts of Franconia suffered terribly. The epidemic subsided in summer 1813 when the lice - typhus is a louse-born disease - were less and better under control. But again in the winter of 1813/14, after the battle of Leipzig (Oct. 1813), a murderous epidemic of typhus broke out and killed very many people in cities like Wurzburg, Aschaffenburg, and Mainz. Mortality rose to a high percentage. Some contemporary German doctors had a rough idea that the carrier of the disease must be in the clothes. According to very conservative estimates one out of ten Germans fell sick, and ten percent of the sick died of typhus, a quarter of a million out of 23 million people. German historiography normally does not mention this epidemic in history text-books, so this epidemic is rather unknown.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.250
Teacher spread0.232 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations15
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicYersinia bacterium, plague, ectoparasites researchFrench-language works237,207