Bibliographic record
Abstract
suggestive evidence that b 2 adrenergic therapy might be able to enhance alveolar lung epithelial repair.The results of this study are important.They provide a new mechanism to potentially explain the beneficial effects of b 2 adrenergic agonist therapy in patients with acute lung injury.The data suggest that repair of the injured alveolus might be accelerated by b 2 agonists, an effect that could provide a functional epithelial barrier that might be better able to remove alveolar oedema fluid in patients with acute lung injury.Although not tested in this study, other investigators have suggested that b 2 adrenergic agonists might also decrease injurious inflammatory responses 17 and reduce lung endothelial injury.18 In summary, the investigators should be commended for an elegant translational study that tests a novel mechanism by which b 2 agonists might benefit the injured lung.Large well powered randomised clinical trials are needed to test the potential value of b 2 agonist therapy in patients with acute lung injury.In the USA, treatment with aerosolised b 2 agonist is currently being tested in a 1000 patient trial by the ARDS Network supported by the National Heart Lung and Blood Institute.Hopefully, a trial of intravenous salbutamol will be carried out with the support of the Medical Research Council in the UK in the near future.
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 | 0.011 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.059 | 0.039 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".