Bibliographic record
Abstract
PURPOSE OF REVIEW: Culture and molecular approaches have established that lower airway infections are polymicrobial. We consider how this new perspective in cystic fibrosis (CF) may affect treatment choices. RECENT FINDINGS: Standard clinical microbiology of CF infection exacerbations often fails to provide indications of microbial causes that may drive the onset of exacerbation and the anticipated bacteriologic responses to the usual parenteral antibiotics prescribed as treatment. Antimicrobial responses by nonclassical members of the CF airway microbiome may explain why most patients clinically improve. These other organisms contribute to disease either directly as pathogens missed by conventional microbiology or through synergy with conventional pathogens. With these considerations, therapy may best be guided by directed antibiotic therapy to numerically significant isolates. An example is the Streptococcus milleri group, which we now believe to represent new pathogens that profile the exacerbations of infection in the CF lung and that necessitate specific antibiotic therapy to prevent loss of lung function and reduce frequency of exacerbations. SUMMARY: A comprehensive understanding of airway infections offers the potential for improved disease management in CF patients. Accurate quantitative microbiology will be a prerequisite for routine intervention based on the polymicrobial perspective of CF infection exacerbations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".