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Record W1997581659 · doi:10.1097/pap.0b013e31820ca329

The Medical Mystery of Napoleon Bonaparte

2011· article· en· W1997581659 on OpenAlexaff
Alessandro Lugli, M. Clemenza, Philip E. Corso, J. di Costanzo, Richard Dirnhofer, E. Fiorini, C. Herborg, John Hindmarsh, E. Orvini, A. Piazzoli, E. Previtali, A. Santagostino, Amnon Sonnenberg, Robert M. Genta

Bibliographic record

VenueAdvances in Anatomic Pathology · 2011
Typearticle
Languageen
FieldMedicine
TopicMethemoglobinemia and Tumor Lysis Syndrome
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersLaboratori Nazionali del Gran Sasso
KeywordsBattleCause of deathMedicineHistoryAncient historyAutopsySAINTDiseasePathologyArt history

Abstract

fetched live from OpenAlex

Napoleon Bonaparte (1769 to 1821) is one of the most studied historical figures in European history. Not surprisingly, amongst the many mysteries still surrounding his person is the cause of his death, and particularly the suspicion that he was poisoned, continue to intrigue medical historians. After the defeat of the Napoleonic Army at the battle of Waterloo in 1815, Napoleon was exiled to the small island of Saint Helena in the South Atlantic, where he died 6 years later. Although his personal physician, Dr François Carlo Antommarchi, stated in his autopsy report that stomach cancer was the cause of death, this diagnosis was challenged in 1961 by the finding of an elevated arsenic concentration in one of Napoleon's hair samples. At that time it was suggested that Napoleon had been poisoned by one of his companions in exile who was allegedly supported by the British Government. Since then Napoleon's cause of death continues to be a topic of debate. The aim of this review is to use a multidisciplinary approach to provide a systematic and critical assessment of Napoleon's cause of death.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.293
Teacher spread0.277 · 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 designCase report
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

Citations12
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Anatomic PathologySame topicMethemoglobinemia and Tumor Lysis SyndromeFrench-language works237,207