An Official American Thoracic Society Workshop Report: Presentations and Discussion of the Fifth Jack Pepys Workshop on Asthma in the Workplace. Comparisons between Asthma in the Workplace and Non–Work-related Asthma
Bibliographic record
Abstract
The fifth Jack Pepys Workshop on Asthma in the Workplace focused on the similarities and differences of work-related asthma (WRA) and non-work-related asthma (non-WRA). WRA includes occupational asthma (OA) and work-exacerbated asthma (WEA). There are few biological differences in the mechanisms of sensitization to environmental and occupational allergens. Non-WRA and OA, when due to high-molecular-weight agents, are both IgE mediated; it is uncertain whether OA due to low-molecular-weight agents is also IgE mediated. Risk factors for OA include female sex, a history of upper airway symptoms, and a history of bronchial hyperresponsiveness. Atopy is a risk factor for OA due to high-molecular-weight agents, and exposure to cleaning agents is a risk factor for both OA and non-WRA. WEA is important among workers with preexisting asthma and may overlap with irritant-induced asthma, a type of OA. Induced sputum cytology can confirm airway inflammation, but specific inhalation challenge is the reference standard diagnostic test. Inhalation challenges are relatively safe, with the most severe reactions occurring with low-molecular-weight agents. Indirect health care costs account for about 50% of total asthma costs. Workers with poor asthma control (WRA or non-WRA) are less likely to be employed. Income loss is a major contributor to the indirect costs of WRA. Overall, asthma outcomes probably are worse for adult-onset than for childhood-onset asthma but better for OA than adult-onset non-WRA. Important aspects of management of OA are rapid and proper confirmation of the diagnosis and reduction of exposure to sensitizers or irritants at work and home.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.033 |
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".