The Prediction of Small Airway Dimensions Using Computed Tomography
Bibliographic record
Abstract
Chronic obstructive pulmonary disease is characterized by destruction of the lung parenchyma and/or small airway narrowing. To determine whether the dimensions of relatively large airways assessed using computed tomography (CT) reflect small airway dimensions measured histologically, we assessed these variables in nonobstructed or mild to moderately obstructed patients having lobar resection for a peripheral tumor. For both CT and histology, the square root of the airway wall area (Aaw) was plotted versus lumen perimeter to estimate wall thickness. The wall area percentage was calculated as wall area/lumen area + wall area x 100. Although CT overestimated Aaw, the slopes of the relationships between the square root of Aaw and internal perimeter (Pi) measured with both techniques were related (CT slope = 0.2059 histology slope + 0.1701, R2 = 0.32, p < 0.01). The mean wall area percentage measured by CT for airways with a Pi of greater than 0.75 cm predicted the mean dimensions of the small airways with an internal diameter of 1.27 mm (R2 = 0.57, p < 0.01). We conclude that CT measurements of airways with a Pi of 0.75 cm or more could be used to estimate the dimensions of the small conducting airways, which are the site of airway obstruction in chronic obstructive pulmonary disease.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".