Can epidemiological studies determine the productivity-related burden of COPD?
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death around the world [1]. Chronic airflow obstruction (CAO), measured by spirometry, is the most commonly used objective characteristic of COPD [2]. Epidemiological research has provided researchers and clinicians with critical information about the burden of COPD and its risk factors; [3–9]; however, very few studies have investigated the productivity-related burden of COPD [10–12]. The Burden of Obstructive Lung Disease (BOLD) study is one of the best designed epidemiological studies investigating prevalence and risk factors for COPD, and has been vital in improving our understanding of COPD around the world [3, 13]. In this issue of the European Respiratory Journal , Grønseth et al. [14] estimate the association between CAO and unemployment at 26 BOLD sites. The study demonstrates that there is greater unemployment in participants with CAO, which was partially confounded by socioeconomic factors. Importantly, the study reports no association in low and middle income countries (LMIC), which emphasises the diversity of risk factors and burden of COPD in different parts of the world. The causal association between chronic airflow obstruction and unemployment is complex and requires further study
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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 | 0.050 | 0.296 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.023 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 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".