Computed Tomographic Imaging of the Airways in COPD and Asthma
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
Computed tomography (CT) is the modality of choice for imaging the airways. Volumetric data sets with isotropic spatial resolution based on multidetector thin-section CT with overlapping reconstruction should be used. Chronic obstructive pulmonary disease and asthma are the 2 most common disease entities that are defined by airflow obstruction. The morphologic correlates of airway changes are dilation of the lumen, thickening of the wall, visibility of small airways due to mucus or edema, air trapping, hypoxic vasoconstriction, and collapsibility. To assess air trapping, additional expiratory low-dose scans are recommended. In clinical routine, these findings are visually assessed and should be routinely reported. However, the interobserver variability is high, and there is a clear need for objective software-based measurements. The development of such tools is challenging, and they are just becoming available on a broader scale. Novel techniques based on dual-energy CT aim to measure iodine distribution maps to assess pulmonary perfusion as well as the distribution of inhaled xenon gas to assess the distribution and time course of pulmonary ventilation. However, these techniques are still being investigated in clinical studies. This review will provide an overview of CT for the diagnosis of chronic obstructive pulmonary disease and asthma, its role in phenotyping these diseases, and the measurement of disease severity and functional compromise.
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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 | 0.000 |
| 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