Airways Disease: Phenotyping Heterogeneity Using Measures of Airway Inflammation
Bibliographic record
Abstract
: Despite asthma and chronic obstructive pulmonary disease being widely regarded as heterogeneous diseases, a consensus for an accurate system of classification has not been agreed. Recent studies have suggested that the recognition of subphenotypes of airway disease based on the pattern of airway inflammation may be particularly useful in increasing our understanding of the disease. The use of non-invasive markers of airway inflammation has suggested the presence of four distinct phenotypes: eosinophilic, neutrophilic, mixed inflammatory and paucigranulocytic asthma. Recent studies suggest that these subgroups may differ in their etiology, immunopathology and response to treatment. Importantly, novel treatment approaches targeted at specific patterns of airway inflammation are emerging, making an appreciation of subphenotypes particularly relevant. New developments in phenotyping inflammation and other facets of airway disease mean that we are entering an era where careful phenotyping will lead to targeted therapy.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".