From infancy and beyond… ensuring a lifetime of hepatitis B virus (HBV) vaccine-induced immunity
Bibliographic record
Abstract
Despite the long-term efficacy and immune persistence observed following HBV vaccination of infants, the need for a booster dose following infant immunization continues to be deliberated. Evidence from HBV booster dose response studies and long-term immunization program reviews are the basis for the recommendation that a vaccine booster is not necessary. However, further studies continue to emerge and highlight the need for standardization among observational studies in order to appropriately compare outcomes. There is an assumption that neonatal and infant (within 12 months of age) vaccine immune responses are equivalent; however, evidence exists for distinct vaccine responses within the first year of life. HBV vaccine programs have evolved over time, particularly regarding the type and dosage of vaccine used. Several universal neonatal immunization programs initially incorporated a 2.5 μg dosage (Recombivax-HB, Merck). This dosage has been shown in multiple long-term studies and meta-analyses to be associated with a lower primary response, decreased antibody persistence over time, and a reduced booster response 10 to 20 years following immunization. Ongoing surveillance of this and other HBV neonatally-vaccinated populations, particularly in low endemic regions, is necessary to understand the impact on long-term protection in order to ensure lifelong protection against hepatitis B infection.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".