What can computed tomography and magnetic resonance imaging tell us about ventilation?
Bibliographic record
Abstract
This review provides a summary of pulmonary functional imaging approaches for determining pulmonary ventilation, with a specific focus on multi-detector x-ray computed tomography and magnetic resonance imaging (MRI). We provide the important functional definitions of pulmonary ventilation typically used in medicine and physiology and discuss the fact that some of the imaging literature describes gas distribution abnormalities in pulmonary disease that may or may not be related to the physiological definition or clinical interpretation of ventilation. We also review the current state-of-the-field in terms of the key physiological questions yet unanswered related to ventilation and gas distribution in lung disease. Current and emerging imaging research methods are described, including their strengths and the challenges that remain to translate these methods to more wide-spread research and clinical use. We also examine how computed tomography and MRI might be used in the future to gain more insight into gas distribution and ventilation abnormalities in 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".