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Record W2799325003 · doi:10.1136/thoraxjnl-2018-211537

Trends in tuberculosis in the UK

2018· letter· en· W2799325003 on OpenAlexaff
Philippe Glaziou, Katherine Floyd, Mario Raviǵlione

Bibliographic record

VenueThorax · 2018
Typeletter
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsCentre for Global Health Research
FundersWorld Health Organization
KeywordsMedicineTuberculosisDemographyIncidence (geometry)Case fatality ratePopulationMortality ratePovertyUrbanizationPediatricsEnvironmental healthSurgeryEconomic growth

Abstract

fetched live from OpenAlex

The industrial revolution, starting in the 18th-century England and coupled with poverty, urbanisation and squalor, created an optimal environment for the propagation of TB.1 One in four deaths were due to TB by the early 19th century.2 Since then, the remarkable decline in the burden of TB at an average annual rate of 3.3% between 1913 and 1940, documented in one of the longest ever recorded time series of data on the burden of TB (figure 1), a notifiable disease in the UK since 1912, was only interrupted by the two world wars. During those years, the temporary peaks in both incidence and mortality were linked to impoverishment of the population and poorer nutrition. In the years following the Second World War, as in other Western European countries, the fall in TB burden significantly accelerated to an average annual decline of 10% between 1955 and 1960 following the advent of modern chemotherapy. This allowed a reduction in transmission and drastically improved the prognosis of the disease, with a case fatality ratio (approximated as the ratio of mortality over incidence) of about 50% in the prechemotherapy era dropping to less than 10% within a decade of the introduction of chemotherapy. A decline in the effective contact rate3 and low TB rates have also been achieved in other settings that have in common a combination of near-universal access to …

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.096
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.058
GPT teacher head0.376
Teacher spread0.318 · 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
GenreCommentary

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

Citations34
Published2018
Admission routes1
Has abstractyes

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