At-a-glance - Pollens, climate and allergies: Quebec initiatives
Bibliographic record
Abstract
Pollen allergies are a major source of seasonal allergic rhinitis in North America. This type of rhinitis affects 17% of adults in Quebec, a marked increase in the last 30 years. Ragweed (Ambrosia artemisiifolia L.) pollens are responsible for 50% to 90% of rhinitis cases. Climate change has played a significant role in the increased prevalence of seasonal allergic rhinitis over the last few decades. In 2015, the Quebec government put in place a strategy to tackle this problem, the Stratégie québécoise de réduction de l'herbe à poux et des autres pollens allergènes [Quebec strategy to reduce ragweed and other allergenic pollens]. Based on solid evidence, the Strategy advocates for co-operation between stakeholders and the integration of control measures into the maintenance practices of municipalities and other large public and private landowners. This article presents the scientific data underpinning the Strategy and initial successes of the action taken under the Strategy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".