Asthma in apprentice workers The birth cohort parallel: Using apprentices as a powerful cohort design for studying occupational asthma
Bibliographic record
Abstract
This chapter presents a review of longitudinal studies of apprentices in trades and professions entailing substantial risks for the development of occupational asthma (OA). Prospective studies of OA enable the assessment of host characteristics before apprentices/workers enter a particular workforce, thus before being exposed to a suspected etiological agent, as well as the early detection of sensitization to a specific work-related antigen and the evaluation of bronchial responsiveness before onset of symptoms of asthma. Since 1973, several cohort studies have been conducted in Europe and Canada among apprentices exposed to high- and low-molecular-weight agents. The investigated outcomes were, apart from OA, work-aggravated asthma, bronchial hyperresponsiveness, work-related symptoms and specific sensitization. The rate of onset of the relevant outcomes was high even after 1 year of training; the implications for setting timing of surveillance programs would be to screen for sensitization and symptoms in the first 2–3 years of apprenticeship. Several host factors assessed at baseline were identified as risk factors for the incidence of work-related outcomes. However, more investigations are needed to explore the extent to which the risk of work-related allergy and asthma increases with exposure characteristics during apprenticeship. Directions for research in the existing cohorts and in future ones are suggested. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".