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Record W1910323910 · doi:10.5858/2008-132-261-dswopa

Did Sir William Osler perform an autopsy at the Johns Hopkins Hospital?

2008· article· en· W1910323910 on OpenAlexaboutno aff
Brendan P. Lucey, Grover M. Hutchins

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsnot available
Fundersnot available
KeywordsAutopsyBiographyMedicineGerontologyHistoryGeneral surgeryPathologyArt history

Abstract

fetched live from OpenAlex

Sir William Osler was the preeminent internist of his time, who also worked as a pathologist for a considerable period during his career. Between 1876 and 1889, he performed nearly 1000 autopsies in Montreal, Quebec, and Philadelphia, Pa. Many authors concluded that Osler stopped performing autopsies once he moved to Baltimore, Md, because the autopsy service was organized under William Welch, the professor of pathology. However, this assertion has been contradicted by a recent biography of Dr Osler. To reexamine this issue, the autopsy records of The Johns Hopkins Hospital and relevant publications were examined. The evidence suggests that Dr Osler was an enthusiastic, and sometimes engaged, observer of Hopkins autopsies but that he did not function as an autopsy prosector.

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)0.003
metaresearch head score (Gemma)0.027
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.030
GPT teacher head0.242
Teacher spread0.212 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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