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Record W2013696728 · doi:10.7202/030824ar

The Impact of Epidemic Influenza: Canada, 1918-1919

2006· article· fr· W2013696728 on OpenAlexvenueaboutno aff
Janice P. Dickin McGinnis

Bibliographic record

VenueHistorical Papers · 2006
Typearticle
Languagefr
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les effets de l'épidémie d'influenza au Canada en 1918 et 1919 comportent de multiples facettes. Malgré les méthodes diverses mises de l'avant pour combattre la maladie, on n'avait pu découvrir une cure adéquate. Parce que la crise fut soudaine, on dût s'organiser en hâte, ce qui entraîna de la confusion et une certaine dose de manque d'information sur les responsabilités dévolues à chaque organisation. Certaines entreprises furent durement touchées; les compagnies d'assurance-vie, par exemple, durent non seulement travailler avec un personnel décimé par la maladie, mais encore vit le nombre de réclamations monter en flèche. Il est possible, par contre, que l'épidémie ait eu quelqu'effet positif sur le règlement de la guerre. Chose certaine, elle a forcé à une réorganisation complète des services de santé au Canada et dans d'autres pays.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.042
GPT teacher head0.404
Teacher spread0.362 · 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

Citations27
Published2006
Admission routes2
Has abstractyes

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