The search for the ultra‐elusive: Can computed cardiopulmonography enhance early detection of gas exchange abnormality?
Bibliographic record
Abstract
While the mechanisms that control breathing during exercise have been called the 'ultra-secret' , the development of clinically useful methods to diagnose abnormalities in pulmonary gas exchange might be called the 'ultra-elusive' .Although many methods have been developed over at least a century, most rarely make it out of the physiology laboratory.The lung is so exquisite in its role as a gas exchanger that many potentially devastating pulmonary conditions do not result in overt signs or symptoms, and therefore patients are not investigated with diagnostic testing, until they are advanced to the point that deleterious pulmonary remodelling is irreversible.The clinical utility of developing a simple, rapid, non-invasive method that is sufficiently sensitive and specific to determine subtle changes in pulmonary gas exchange could therefore make an important impact in earlier diagnosis and treatment of many obstructive, restrictive, fibrotic or pulmonary vascular diseases.Inert gas washout techniques have been extensively used to better understand heterogeneity of pulmonary deadspace, ventilation and perfusion.In his pioneering work from almost 75 years ago, Ward
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".