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Record W7095639803

A light on medical practice in 19th-century Canada: the medical

2015· article· en· W7095639803 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedical practiceRelevance (law)Relation (database)Clinical PracticeMedical recordMedical knowledgeMedical literatureWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

DURING HIS LONG CAREER AS A PHYSICIAN in Charlottetown, Dr. John Mackieson (1795–1885) compiled 4 medical manuscripts: 2 sets of case records, a synopsis of the medical conditions that were common in his day and a formulary. As primary sources, these documents provide information about medicine in 19th-century Canada and augment our knowledge of the problems of medical practice in that era. They illustrate aspects of the work of Dr. Mackieson, a generalist with interests in surgery and obstetrics, and they facilitate an understanding of the rationale under-lying the treatments that he and his contemporaries used. Although 150 years old, the case records can be appreciated for their relevance to the art of medicine. Two excerpts from the case records, presented in this article, provide a sense of Dr. Mackieson’s writings and introduce a discussion on the significance of these manu-scripts in relation to the ideas on disease and treatment that governed medical prac-tice, both in Prince Edward Island and elsewhere in Canada, in the 19th century.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.249
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0500.050
Scholarly communication0.0140.004
Open science0.0020.004
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.353
Teacher spread0.326 · 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 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
Published2015
Admission routes1
Has abstractyes

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