Report of a workshop: quantitative computed tomography scanning in longitudinal studies of emphysema
Bibliographic record
Abstract
It has been reported that quantitative computed tomography (CT) scanning of the lungs showed decreased progression of emphysema in a randomised clinical trial in patients with severe alpha1-antitrypsin (alpha1-AT) deficiency receiving monthly intravenous augmentation therapy with human alpha1-AT. Comparable results were not obtained using rate of decline of forced expiratory volume in one second. Accordingly, the Alpha-1 Foundation convened a workshop to explore the feasibility of using quantitative CT data as a primary outcome variable in trials of drugs for treating alpha1-AT deficiency. This report reviews the following: the principles for the use of modern CT scanners for quantifying emphysema; the methods and data on validation by comparison with measurements of severity of emphysema in inflation-fixed specimens of lungs; and the possibility of decreasing radiation dosage from CT to make it safe and ethically possible to use CT in longitudinal studies. The workshop concluded that it is feasible, safe and ethically possible to use computed tomography in longitudinal studies of emphysema. It recommended that the primary end-point should be a significant shift in the 15th percentile of lung density.
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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 | 0.062 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.021 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".