Bibliographic record
Abstract
This article offers a review of the potential influences of personal lifestyle on respiratory health in children, looking at both healthy individuals and those with respiratory disorders. As with many aspects of health, regular physical activity, an appropriate diet, and avoidance of obesity and cigarette smoke all contribute to optimal development of the healthy child. An active lifestyle is associated with greater static and dynamic lung volumes, greater efficiency of the ventilatory process, and an optimization of breathing patterns. The risk of upper respiratory infections is also reduced in those maintaining a moderate level of physical activity. Maternal smoking during pregnancy, as well as active and passive smoking, all have an adverse influence on lung function in the child, the largest effects being on dynamic lung volumes. The risk of developing asthma seems reduced in children who maintain a normal body mass and are physically active. A program of graded physical activity is of therapeutic value in a number of established respiratory conditions, including asthma, cystic fibrosis, and ventilatory impairment from neuromuscular disorders. Exercise carries a slight risk of fatalities from asthma and anaphylactic reactions. In designing an optimal physical activity program, it is also important to guard against the hazards of deep oronasal breathing, including the precipitation of bronchospasm by the inhalation of cold, dry air and pollens; an increased exposure to atmospheric pollutants (reducing and oxidant smog, fine and ultra-fine particulates, and carbon monoxide); and possible long-term dangers from chlorine derivatives in the atmosphere of indoor swimming pools.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".