Bibliographic record
Abstract
Bronchiectasis is a common chronic lung disease that remains undertreated and under serviced, likely in part due to its heterogenous nature and diversity in clinical presentation. Bronchiectasis is characterized by the permanent dilation of the airways visible on radiographic imaging, characterized by decreased function of the mucociliary transport mechanism. This dysfunction leads to recurrent infections secondary to increased bacterial invasion and mucus accumulation. It is defined as a syndrome marked by chronic cough, sputum production, and repeated lower respiratory tract infections. Bronchiectasis is an important area of respiratory medicine given its increasing prevalence. It affects an estimated 566 individuals per 100,000, making it the third most common chronic airway disease, after chronic obstructive pulmonary disease and asthma. While it can develop in childhood, particularly during the pre-antibiotic era, it can occur at any age, with prevalence increasing with advancing age. This increase in prevalence may be secondary to greater awareness amongst healthcare professionals. Bronchiectasis is a treatable but rarely curable condition. Identifying and treating the underlying cause is recommended. Bronchiectasis can be caused by many underlying etiologies, including infectious, inflammatory, genetic, or immunological causes. Despite this wide range of etiologies, idiopathic bronchiectasis accounts for 32%–66% of all causes. Treatment goals include managing any underlying systemic conditions, preventing lung infections, and implementing chest physiotherapy. Surgery may be recommended for localized bronchiectasis with refractory infections and hemoptysis. This article will review the chronic management of bronchiectasis, with a focus on chest physiotherapy techniques and the use of inhaled antibiotics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".