Bibliographic record
Abstract
It is estimated that the world population will reach a record 7.3 billion in 2015, and the high burden of chronic conditions associated with ageing and smoking will increase further. Respiratory diseases in general receive little attention and funding in comparison with other major causes of global morbidity and mortality. In particular, chronic obstructive pulmonary disease (COPD) has been a major public health problem and will remain a challenge for clinicians within the 21st century. Worldwide, COPD is in the spotlight, since its high prevalence, morbidity and mortality create formidable challenges for health-care systems. This review emphasizes the magnitude of the COPD problem from a clinician's standpoint by drawing extensively from the new findings of the Global Burden of Disease study. Updated, distilled information on the population distribution of COPD is useful for the clinician to help provide an appreciation of the relative impact of COPD in daily practice compared with other chronic conditions, and to allocate minimum resources in anticipation of future needs in care. Despite recent trends in reduction of COPD standardized mortality rates and some recent successes in anti-smoking efforts in a number of Western countries, the overarching demographic impact of ageing in an ever-expanding world population, joined with other factors such as high rates of smoking and air pollution in Asia, will ensure that COPD will continue to pose an ever-increasing problem well into the 21st century.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".