Development of vaccines against common colds
Bibliographic record
Abstract
Respiratory tract viruses are particularly significant causes of illness and death in children and in the elderly. Vaccines offer the possibility of decreasing the severity and complications of viral respiratory disease, but development has been delayed by numerous factors. First, there are more than 200 serologically distinct RNA and DNA virus species and strains which cause an essentially similar spectrum of disease. Some re-infect at high efficiency despite little antigenic variation, while others exhibit extensive coat protein variability. Vaccine candidates show variable efficacy in partially immune adults, the immunocompromised and the elderly, and may be ineffective or pathogenic in neonates or in the presence of maternal antibodies. However, effective childhood vaccines are essential to prevent severe disease due to respiratory syncytial virus (RSV) and parainfluenza and to reduce virus transmission to adults. A number of promising vaccines are in clinical trial, and it is likely that vaccines against RSV and parainfluenza will be licensed within the next 5-10 years. Mucosal delivery and the use of novel adjuvants offers the prospect of better vaccines against influenza. The ultimate goal is to develop multivalent mucosal vaccines offering protection against a spectrum of respiratory infections.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".