Exacerbations in non-COPD patients: truth or myth—authors’ response
Bibliographic record
Abstract
Exacerbations in non-COPD patients: truth or mythauthors' response Dear Sir, We are grateful to Dr Khurana and Dr Aggarwal for their interest 1 in our paper. n their first point, we agree that we should be careful about terminology. We evaluated a random sample of individuals representative of the general population rather than patients, so the findings that episodes of respiratory events occurred in these subjects would likely reflect real events in the general population. Furthermore, our study definition for exacerbations was the same standard questionnaire criteria for exacerbations used in clinical trials of selected patients with COPD. We excluded those individuals with selfreported chronic obstructive lung diseases, namely, COPD, chronic bronchitis, emphysema and asthma and evaluated bronchodilator reversibility but did not perform bronchoprovocation test. Thus, residual confounding by undiagnosed asthma or bronchiectasis remains. We could not address other specific aetiologies in this study, and further data would require linkage to administrative databases and longitudinal follow-up of the cohort.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".