Bibliographic record
Abstract
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 …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".