Screening for Occupational Asthma by Using a Self-Administered Questionnaire in a Clinical Setting
Bibliographic record
Abstract
OBJECTIVE: Because of its high prevalence, early screening for occupational asthma (OA) is crucial. We aimed to evaluate the screening performance of the Occupational Asthma Screening Questionnaire-11 items (OASQ-11) in a clinical setting. METHODS: Between January 2009 and December 2011, 169 workers referred for potential OA to our hospital completed the OASQ-11 and underwent workups to determine the final diagnosis. The discriminative abilities of the OASQ-11 as a whole and in relation to demographic and exposure parameters were determined by the area under the receiving operator characteristic curve (AUC). RESULTS: Model 1, consisting of the OASQ's items, showed fair discrimination (AUC, 0.69; 95% confidence interval, 0.58 to 0.80). Addition of age and exposure duration to model 1 improved discrimination (AUC, 0.80; confidence interval, 0.72 to 0.88). CONCLUSION: A simple model consisting of the OASQ-11's items, age, and exposure duration could well discriminate subjects with OA in a clinical setting.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".