MétaCan
Menu
Back to cohort
Record W4388769342 · doi:10.1515/9781552384572

Suitable for the Wilds

2006· book· en· W4388769342 on OpenAlexaboutno aff
Dr Mary Percy Jackson

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2006
Typebook
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The plea was advertised in the British Medical Journal in February 1929: seeking "strong energetic Medical Women with post-graduate experience in Midwifery" for "country work" in western Canada. A young Dr. Mary Percy was intrigued. After graduating with degrees in medicine and surgery from the University of Birmingham in 1927, she had been searching for the kind of opportunity which would offer both adventure and practical experience. She answered the advertisement and set off for the Peace River region of Northern Alberta in June of 1929. Little did she know that her "adventure" in the Canadian north was to last more than seventy years. Suitable for the Wilds : Letters from Northern Alberta, 1929-1931, is a collection of Dr. Mary Percy Jackson's letters written to family and friends in the early years of her practice, from 1929-1931. The letters offer a fascinating glimpse at life in northern Alberta at the beginning of the Depression, when the area was being farmed and settled by new European immigrants. These homesteaders, along with the area's Aboriginal and Métis population, were Dr. Percy's patients, scattered throughout a territory covering nearly 400 square miles. Vigilant about vaccination, nutrition, and preventive medicine, she quickly proved to be a talented physician who was truly ahead of her time, particularly in the area of tuberculosis treatment and prevention. Dr. Percy's dedication, good nature, and unfailing sense of humour shine through in her letters. This delightful and captivating collection is a tribute to her indomitable spirit.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.052
Threshold uncertainty score0.426

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.167
Teacher spread0.156 · 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
GenreOther

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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Calgary Press eBooksSame topicPlant Ecology and Soil ScienceFrench-language works237,207