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Record W4384524191 · doi:10.4081/reumatismo.2023.1570

Arthur Conan Doyle, Sherlock Holmes, and gout

2023· article· en· W4384524191 on OpenAlexaboutno aff
Ernesto Damiani

Bibliographic record

VenueReumatismo · 2023
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdventureQuarter (Canadian coin)Context (archaeology)GoutMedical literatureWifeLiteraturePsychoanalysisArt historyHistoryArtPsychologyPathologyTheologyPhilosophy

Abstract

fetched live from OpenAlex

Arthur Conan Doyle, the creator of Sherlock Holmes, was an experienced physician who treated gouty patients. A gouty character appears in The Adventure of the Missing Three-Quarter, a Sherlock Holmes novel. This offers the possibility of discussing gout from the peculiar perspective of a medical writer in light of the historical-medical context of the time. This study was conducted using Conan Doyle's autobiographical, scientific, and literary primary sources, as well as past and current medical literature. The Adventure of the Missing Three-Quarter was autobiographical. Conan Doyle himself was a rugby player and his wife died of tuberculosis. Furthermore, in 1884, in The Lancet, he described the hereditary case of a female gouty patient, presenting with ocular manifestations. In agreement with the concept of rich man's gout, the gouty patient of Sherlock Holmes' story, Lord Mount James, was a rich irascible noble but he was not addicted to the pleasures of food and sex. Following the usual funny representation of gouty patients, Conan Doyle made fun of Lord Mount James, but he misquoted a true case of gout cited in the literature. In his scientific and literary production on gout, Conan Doyle stuck to the most updated medical concepts of the time, demonstrating an uncommon knowledge of scientific literature.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.001

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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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