Bibliographic record
Abstract
Allergic rhinitis (AR) is highly prevalent in Canada, affecting approximately 20–25% of the population. Asthma is estimated to affect approximately three million Canadians, and between 12% and 25% of Canadian children. Approximately two-thirds of individuals with asthma are allergic to aeroallergens, and these allergens act as triggers for asthma exacerbations. Overall, approximately 7.7 million individuals were affected by aeroallergens in Canada in 2016. High concentrations of ambient aeroallergens, including tree pollen and fungal spores have been associated with increased risk of premature birth, myocardial infarction (MI) and asthma-related Emergency Department visits and hospitalizations in cities across Canada. This demonstrates that nation-wide aeroallergen counts are associated with severe signs and symptoms. Children exposed to various indoor allergens are placed at an increased risk of developing asthma in later life, with sensitization in these individuals being a strong predictor of disease morbidity. Common indoor exposures for infants include house dust mite, pet, cockroach, mould, and rodent allergens. Sensitization to at least one indoor allergen has been demonstrated to be present in nine of every ten children hospitalized with asthma. It has been noted that more than 90% of children worldwide breathe polluted air. While the impact of climate change on aeroallergen exposure is not fully understood, there is increasing evidence that it may have an impact on outdoor aeroallergens and, by extension, asthma control in children. Global warming has been projected to influence the duration and intensity of pollen seasons, and may lead to increased pollen production, prolonged pollen seasons, and increased pollen protein allergenicity. The changing weather patterns including rainfall and wind may cause pollen species to reach environments in which they had not previously been present, contributing to a shift in geographic pollen distributions.
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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".