Bibliographic record
Abstract
Approximately two-thirds of cases of chronic obstructive pulmonary disease (COPD) and adult asthma are in part driven by impaired lung development related to early-life events. Many children who suffer insults to their lungs during the first few years of life experience abnormal lung development, growth, and/or maturation, leading to impaired lung function, which may persist throughout their lifespan. This abnormal lung trajectory may be exacerbated by lung dysanapsis, genetic and epigenetic alterations, oxidative stress and/or inflammation in the airways related to environmental factors including exposure to active or secondhand smoke, air pollution, poor nutrition and social deprivation, and repeated childhood respiratory tract infections. Children with asthma may transition to COPD in adulthood if their asthma is poorly controlled or in the presence of other risk factors such as smoking. As many of these factors are modifiable, prompt diagnosis and implementation of preventive measures should be considered as early as possible in children at risk for abnormal lung development. This review provides an update on the interplay between genetic, environmental, and socioeconomic factors, their cumulative impact on lung development, and its implication for the risk and burden of asthma and COPD in the global population.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".