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Record W4298010179 · doi:10.3138/cjhh.2022-548-102021

On the Issue of the Spanish Flu in the First Czechoslovak Republic

2022· article· en· W4298010179 on OpenAlexvenueno aff
Andrej Tóth, Inka Kratochvílová, Jakub Drábek, Lukáš Novotný, Věra Hellerová, Martin Červený, Valérie Tóthová

Bibliographic record

VenueCanadian Journal of Health History · 2022
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicGovernment (linguistics)Influenza pandemicHealth carePopulationState (computer science)The RepublicPolitical scienceWork (physics)Coronavirus disease 2019 (COVID-19)Economic growthGeographyInfectious disease (medical specialty)DemographyMedicineDiseaseEnvironmental healthLawSociology

Abstract

fetched live from OpenAlex

The aim of this paper is to summarize the impact of Spanish influenza on the Czechoslovak Republic, examine the spread of Spanish influenza, and analyze its impact on the mortality of the population. The work is based on an analysis of mostly secondary historical sources containing information on the Spanish flu during the Czechoslovak Republic. Although the new Czechoslovak state paid significant attention to the healthcare system from its beginning, official government statistics do not offer enough relevant data to reconstruct the struggle of the healthcare system with the Spanish flu or determine the consequences of this pandemic in terms of population mortality. The expected number of deaths from Spanish influenza in the Czechoslovak Republic can be calculated using mathematical methods and relevant data. The Spanish flu pandemic tested the readiness of hospitals and nursing care to fight infectious disease of the new created state.

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)0.011
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.706
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.262
Teacher spread0.228 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Health HistorySame topicHealth Promotion and Cardiovascular PreventionFrench-language works237,207