Bibliographic record
Abstract
BACKGROUND: There is currently little information regarding how much the distribution of research activity in respiratory medicine reflects the interests of its clinicians and scientists, the disease burden in any country, or the availability of funding. METHODS: A total of 81,419 respiratory medicine publications identified in the Science Citation Index for the years 1996-2001 were assigned to 14 subject areas (mainly based on title words) and to 15 OECD countries. Outputs were compared with a nation's disease burdens and, for the UK, the sources of research funding were investigated. RESULTS AND CONCLUSIONS: Overall, Finland, Canada, Spain and the UK had the greatest relative commitment to respiratory medicine research expressed as a ratio of their share of world biomedical research. The largest subject areas were asthma, lung cancer, and paediatric lung disease, each with over 1400 papers published per year. Australia and Canada led in relative commitment to sleep research and Sweden and Finland led in research on asthma. Australia and the UK produced significant numbers of publications on cystic fibrosis (CF) but Finland produced few. The Netherlands has a strong output on chronic obstructive pulmonary disease (COPD), France and the UK on diffuse parenchymal lung disease (DPLD), and Finland dominated occupational lung disease research but had few publications on HIV/AIDS where Spain proportionately produced most. Finland and Australia had strong outputs in paediatric lung disease research. For most subject areas the research output of a country correlated poorly with disease burden. In the UK, lung cancer research appeared unduly low in relation to the number of deaths and COPD outputs were low compared with those for asthma. However, correlations were positive for the burden of CF and pulmonary complications of HIV/AIDS which explains, for example, the low outputs in these subject areas from Finland. The strong performance in CF research in the UK is likely to reflect significant charitable funding, while sleep research, pulmonary circulatory disease, and DPLD had little stated external funding or sponsorship.
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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 | 0.026 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.033 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.132 | 0.055 |
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".