Editorial: Recent advances in the development of vaccines against Acinetobacter baumannii
Bibliographic record
Abstract
Acinetobacter baumannii is a notorious Gram-negative healthcare-associated (nosocomial and community-acquired) bacterial pathogen that causes a high mortality rate (up to 70%). The rapid emergence of highly antibiotic-resistant strains is a further propellant to introduce the bacterium as a serious public health threat. Hence, the World Health Organisation (WHO) listed A. baumannii (carbapenem-resistant) as the first priority that needs new antibiotics. The recent coronavirus disease 2019 (COVID-19) pandemic further increased the outbreak of carbapenem-resistant A. baumannii infections. Many novel antibiotics were introduced into the market but few are effective against A. baumannii. Hence, further approaches such as immunization trials had been considered as alternative solutions against A. baumannii infections. Several antigens had been introduced for active and passive immunizations. An effective robust immunization should develop full protection against various types of infections and all pathogenic strains. Moreover, it should have no deleterious effect on microbiota as well as the human proteome. Despite rigorous basic and pre-clinical studies conducted on active and passive immunizations against this pathogen, no vaccine has been advanced to clinical trials. Recently, the combination of protective antigens, epitopes/peptides or presentation of protective epitopes by appropriate scaffold had been suggested as effective promising approaches against A. baumannii.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".