Bibliographic record
Abstract
Influenza vaccination with current inactivated vaccines homologous to the prevalent wild-type virus can reduce influenza illness in 75%-80% of healthy adults. Vaccine is recommended for all individuals with chronic underlying diseases and for those aged 65 years or older. Although influenza vaccination is still advocated for patients with blunted immunity, protection rates are not as high, running at 40% for frail institutionalized elderly people. The influenza antiviral agents amantadine or rimantadine, zanamivir and oseltamivir can modify the severity of illness and reduce the duration of illness by about 1.5-2.5 days. Amantadine inhibits only influenza A. Resistant virus may emerge in up to 33% of amantadine-treated patients in the first 5 days of treatment and be transmitted to susceptible close contacts. Side effects are usually mild in short courses of treatment. The neuraminidase inhibitor drugs zanamivir and oseltamivir act on both influenza A and B. Treatment is most effective when given within 30-36 hours after the onset of illness, and the earlier the better. Influenza should be treated with antiviral drugs in unvaccinated and vaccinated high-risk patients, as well as immunosuppressed patients with influenza-like illness, in periods of confirmed influenza prevalence. These drugs may be of great value in the event of a major viral antigenic shift that causes pandemic influenza, if an adequate supply can be sustained.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".