Influvac Tetra: clinical experience on safety, efficacy, and immunogenicity
Bibliographic record
Abstract
INTRODUCTION: This paper summarizes the safety and immunogenicity data of Influvac Tetra across all age groups starting from 6 months of age, obtained during its clinical development program. AREAS COVERED: The article covers the clinical development program of Influvac Tetra based on five registration studies that included different age groups, different comparators, and participants from Europe and Asia. Safety and immunogenicity were assessed in all studies and in one study, the efficacy of Influvac Tetra was assessed. EXPERT OPINION: Seasonal influenza is a vaccine-preventable disease that can cause serious complications. Several types of influenza vaccines are available, including egg-based (standard dose, high dose, and adjuvanted), cell-based, and recombinant. The COVID-19 pandemic has stimulated innovation in the development such as mRNA vaccines. However, these vaccines are still in development and the true value still has to be proven. Regardless of the type of vaccine, it is also important to increase overall vaccination coverage. ECDC recommends that EU Member States implement action plans and policies aimed at reaching 75% coverage in at-risk groups and healthcare workers. Even so, vaccine coverage is still far from recommended.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".