[New microbiological data on the susceptibility of Pneumococci to levofloxacin].
Bibliographic record
Abstract
INCREASINGLY WIDESPREAD USE OF THE NEW FLUOROQUINOLONES: For the treatment of airway infections raises the risk of bacterial resistance, particularly for Streptococcus pneumoniae. IN FRANCE, PRESCRIPTIONS FOR QUINOLONES: Are much less frequent than in several other large countries. This is also true for anti-pneumococcal fluoroquinolones although prescriptions have increased moderately over the last year. FURTHER TO THE CONCERNS RESULTING: From the publication of two studies from Canada and Hong Kong in 1999 that suggested an increasing rate of fluoroquinolone resistant pneumocci, it has been established that the real rate of isolation of resistant strains remains very low, particularly in France, while the rate of penicillin and macrolide resistant strains has been more than 50% in most studies. S. PNEUMONIAE RESISTANCE: Basically results from chromosomal mutations that inhibit the affinity of fluoroquinolones for intrabacterial targets (topoisomerase i.v. and gyrase DNA), or increase active exflux. ALTHOUGH THE CURRENT OUTLOOK IS RATHER OPTIMISTIC: It is nevertheless indispensable to implement preventive measures for prescriptions and personal health care in order to limit the emergence and dissemination of fluoroquinolone-resistant penumococcal strains.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".