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Record W2167917112 · doi:10.1093/shm/hkp074

A Surgeon in the Army of the Potomac

2009· article· en· W2167917112 on OpenAlexaffabout
Jonathan Allard

Bibliographic record

VenueSocial History of Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsBrock University
Fundersnot available
KeywordsQueen (butterfly)Library scienceHistoryGerontologyMedicineComputer science

Abstract

fetched live from OpenAlex

Journal Article A Surgeon in the Army of the Potomac Get access Francis M. Wafer, A Surgeon in the Army of the Potomac, edited by Cheryl A. Wells, Montreal and Kingston: McGill-Queen's University Press, 2008. Pp. xliv + 225. (CAN) $ 34.95/US$ 29.95. ISBN 978 07735 3381 3. James Robert Allard James Robert Allard Brock University jallard@brocku.ca Search for other works by this author on: Oxford Academic PubMed Google Scholar Social History of Medicine, Volume 22, Issue 3, December 2009, Pages 630–632, https://doi.org/10.1093/shm/hkp074 Published: 03 November 2009

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.307
Teacher spread0.270 · 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 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

Citations1
Published2009
Admission routes2
Has abstractyes

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