Reply to Brusasco and Pellegrino
Bibliographic record
Abstract
In 1999, i.e., long before the acronym PRISm was coined, Aaron and colleagues (3) stated that ",60% of patients with a classical spirometric restrictive pattern had pulmonary restriction confirmed on lung volume measurements."Said in other words, a spirometric pattern with a reduction of FVC and a normal FEV 1 /FVC ratio could be consistent with decreased total lung capacity, i.e., restriction or increased residual volume, i.e., obstruction or expiratory muscle weakness, conditions that can be differentiated only by measuring absolute lung volumes.This was strongly recommended by the American Thoracic Society/European Respiratory Society documents on lung function testing of 2005 (4) and 2022 (5).One would argue that matching BD response with clinical questionnaires could help in interpreting the PRISm pattern, though others may not support this approach because of the variety of conditions that are possibly associated with PRISm, the nonspecific nature of respiratory symptoms, and the variability of acute BD responses.In conclusion, the results of Magner and coworkers' study (1) reinforce our conviction that PRISm is a mere description of what the spirometry numbers already say, void of any physiological interpretation.We agree with the authors that subjects with PRISm require additional investigation, which is certainly preferable to a wait-and-see approach, but the first one should be the measurement of absolute lung volumes.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.043 | 0.038 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".