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Record W2131221739

Lupus pernio: a tale of four characters in search of a malady.

2009· letter· en· W2131221739 on OpenAlexaboutno aff
O. P. Sharma, Ιlias Papanikolaou

Bibliographic record

VenuePubMed · 2009
Typeletter
Languageen
FieldMedicine
TopicSarcoidosis and Beryllium Toxicity Research
Canadian institutionsnot available
Fundersnot available
KeywordsSAINTBeautyEleganceArt historyMedicineArtCartographyClassicsGeographyLiterature
DOInot available

Abstract

fetched live from OpenAlex

Honfleur, an old picturesque port, sits on the southern estuary of the Seine, one of the principal rivers of France. Many artists, including Gustave Courbet, Claude Monet, John Jongkind and Eugene Boudin have immortalized its beauty, serenity, and natural elegance. The explorer Binot Paulmierde Gonneville set forth from its shores in 1503 to explore Brazil. Another navigator, Jean Denis left Honfleur in 1608 to found Newfoundland and the mouth of Saint Lawrence River. Other famous Honfleurais have included Alphonse Allais, writer and humorist: Erik Satie, musician; and Stephane Ferrand, wildlife photographer. In 1859, Baudelaire ravaged by his illnesses, long-term use of laudanum and absinthe, stress and poverty, moved to Honfleur to live with is mother. He was at peace in the seaside town where wrote Le Voyage. Ernest Besnier, one of the characters of our tale was also born in Honfleur on April 21, 1831 (Fig. 1). His father was a government official on the move. As a result, the young Besnier was schooled in different places, including Honfleur, Marseilles, and Orleans. Finally, he settled in Paris to study Medicine. He worked hard and won the first prize of the Internat des Hopitaux de Paris in 1853. He was then 22 years old. In 1867, at 32 years of age, Besnier secured his Doctor of Medicine degree and joined the Institution Saint Perrine. He stayed there for 10 years and published several epidemiological reports on the then prevalent diseases. In 1873, he was moved to the Hopital Saint Louis to occupy the Chair in Dermatology vacated by the retirement of Bazin. An intellectually honest man, Besnier worked for a quarter of a century in complete harmony with his medical colleagues and his patients. He was an outstanding teacher, had a large clinical practice, and was an able administrator and organizer. He built an annex to the hospital with complete histopathology and parasitology laboratories. He introduced the word “biopsy” to describe the techLupus pernio: a tale of four characters in search of a malady

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)0.002
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: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0070.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.003

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 head0.060
GPT teacher head0.283
Teacher spread0.223 · 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
GenreCommentary

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

Citations5
Published2009
Admission routes1
Has abstractyes

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