Bibliographic record
Abstract
Acute exacerbations of chronic bronchitis are one of the major public health challenges. New data suggest that they will remain so for many years. Although the role of bacteria in the initiation and maintenance of bronchial inflammation, both during and between exacerbations, is well recognized, studies of the long-term effects of therapy are few and inadequate, and the nature of the relationship with disease progression is largely unknown. Data are beginning to emerge that firmly link bacterial inflammation and progressive disease with physiological and functional disability. Methods are being developed to provide integrated, uncomplicated and reproducible assessments of health-related quality of life. These may prove fundamental to the proper investigation of new treatment modalities. Among the newer antibacterial agents, fluoroquinolones have received most investigative attention, regrettably usually without providing clinical confirmation of their obvious superiority in vitro and of their pharmacokinetic and related pharmacodynamic properties. New trial designs need to address an integrated outcome analysis, with the assessment of long-term benefit and pharmaco-economic monitoring. More antibacterial agents are available at the millennium than ever before. After 50 years, it would be preferable if we knew a little more about their role in this complex disease.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".