<i>This</i> is what <scp>COPD</scp> looks like
Bibliographic record
Abstract
Despite decades of research, and the growing healthcare and societal burden of chronic obstructive pulmonary disease (COPD), therapeutic COPD breakthroughs have not occurred. Sub-optimal COPD patient phenotyping, an incomplete understanding of COPD pathogenesis and a scarcity of sensitive tools that provide patient-relevant intermediate endpoints likely all play a role in the lack of new, efficacious COPD interventions. In other words, COPD patients are still diagnosed based on the presence of persistent airflow limitation measured using spirometry. Spirometry measurements reflect the global sum of all the different possible COPD pathologies and perhaps because of this, we lose sight of the different contributions of airway and parenchymal abnormalities. With recent advances in thoracic X-ray computed tomography (CT) and magnetic resonance imaging (MRI), lung structure and function abnormalities may be regionally identified and measured. These imaging endpoints may serve as biomarkers of COPD that can be used to better phenotype patients. Therefore, here we review novel CT and MRI measurements that help reveal COPD phenotypes and what COPD really 'looks' like, beyond spirometric indices. We discuss MR and CT imaging approaches for generating reproducible and sensitive measurements of COPD phenotypes related to pulmonary ventilation and perfusion as well as airway and parenchyma anatomical and morphological features. These measurements may provide a way to advance the development and testing of new COPD interventions and therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".