Noninvasive methods for assessment of airway inflammation in occupational settings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To cite this article: Quirce S, Lemière C, de Blay F, del Pozo V, Gerth Van Wijk R, Maestrelli P, Pauli G, Pignatti P, Raulf‐Heimsoth M, Sastre J, Storaas T, Moscato G. Noninvasive methods for assessment of airway inflammation in occupational settings. Allergy 2010; 65 : 445–458. Abstract The present document is a consensus statement reached by a panel of experts on noninvasive methods for assessment of airway inflammation in the investigation of occupational respiratory diseases, such as occupational rhinitis, occupational asthma, and nonasthmatic eosinophilic bronchitis. Both the upper and the lower airway inflammation have been reviewed and appraised reinforcing the concept of ‘united airway disease’ in the occupational settings. The most widely used noninvasive methods to assess bronchial inflammation are covered: induced sputum, fractional exhaled nitric oxide (FeNO) concentration, and exhaled breath condensate. Nasal inflammation may be assessed by noninvasive approaches such as nasal cytology and nasal lavage, which provide information on different aspects of inflammatory processes (cellular vs mediators). Key messages and suggestions on the use of noninvasive methods for assessment of airway inflammation in the investigation and diagnosis of occupational airway diseases are issued.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it