Domestic endotoxin exposure and asthma in children epidemiological studies
Bibliographic record
Abstract
Homes contain low but measurable concentrations of endotoxin that have been linked to household conditions such as the presence of animals, smoking, crowding, and farm living. While endotoxin exposure in early life appears to have a protective effect for childhood asthma; the evidence from prospective cohort studies of young children suggests that endotoxin exposure contributes to early development of wheeze. Higher domestic endotoxin levels are linked to greater asthma severity in school age children unless children are farm residents where, higher doses of farm-related endotoxin seem to offer some protection against asthma. Currently there are inconsistencies between epidemiological studies examining the role of endotoxin and children's respiratory health that may be due, in part, to selection bias of study populations, timing between measurement of endotoxin levels and the assessment of asthma symptoms. Although there is good evidence to demonstrate that endotoxin exposure in homes is associated with wheeze in children, and less likely to be associated with asthma, understanding the mediating roles of atopy, genetic and other environmental factors requires further and extensive exploration.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| 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) | 0.004 | 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".